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08:25 Status bar
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In this video I talk about where exactly to start your data science learning journey. This is one of the most frequent questions that I get. Hopefully this will shed some light on your path and give you a concrete starting point.

Unfortunately, everyone learns data science a little differently. What works for me may not work for you.

It matters less where you start learning and more when. You should start right now and choose a course, certificate or project. Just do it. Most of the resources out there are very good, and you won't notice a difference as you learn more.

Once thing people don't realize is that learning data science is additive. If you want to take multiple courses, go ahead! No one learns data science from a single source. I have learned data science concepts from my schoolwork, projects, certificates, other people, etc. You shouldn't think one certificate will teach you everything.

Again, these are my best tips on where to start learning data science!

Best free data science courses: https://www.youtube.com/watch?v=Ip50cXvpWY4

Always be curious and love the struggle!
#DataScience #KenJee

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Data science is not going away. People are willing to alter their major in order to seek a job in data science. But that begs the question, what do Data Scientists do? What problem statements do they work on?

Here's Srikanth Varma, (SVP (Data Science & ML), Scaler) answering one of the most asked questions by data science enthusiasts.

What is Data Science?
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains.

What is Machine Learning?
Machine learning (ML) is a subset of artificial intelligence (AI) that enables software applications to grow increasingly effective at predicting outcomes without explicitly programming them to do so. In order to forecast new output values, machine learning algorithms use historical data as input.

Who are Data Scientists?
Data scientists choose the questions their team should pose and work out how to use data to provide answers. They frequently create predictive models for forecasting and theorising.

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Developer communities are one of the best ways to get updated with all the newest technologies and tools in the tech space. With the rise in demand for machine learning and data science among the organisations, enthusiasts are either choosing their ML journey from scratch or switching their roles. Joining the machine learning communities, one can have several benefits, including sharing tools and support, answering queries, mentorship, code reviews and much more.
Join My telegram group: https://t.me/joinchat/N77M7xRvYUd403DgfE4TWw

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https://github.com/open-source

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https://www.reddit.com/r/MachineLearning/

This is the realistic route I would take with some bonus projects.

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This trailer is for the online Specialization, IBM Data Science Professional Certificate. Enroll today at https://www.coursera.org/specializations/ibm-data-science-professional-certificate?utm_source=yt&utm_medium=social&utm_campaign=channel&utm_content=ibm to get access to the full specialization!

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It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics.

Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science.

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In reality, data science work often involves more data cleaning, preprocessing, and feature engineering than the more glamorous tasks like model building and deployment. The difference between what is learned in academia and what is practiced in industry is often due to the emphasis placed on different aspects of the work, with academia emphasizing the theory and industry emphasizing practical applications and problem-solving. Additionally, data privacy and ethical considerations are often not addressed in detail in academic settings, but are crucial in industry.
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Check Out My Other Playlist
Python Playlist:
Python In English:https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVNUL99R4bDlVYsncUNvwUBB

Python In Hindi: https://www.youtube.com/watch?v=MJd9d9Mpxg0&list=PLTDARY42LDV4qqiJd1Z1tShm3mp9-rP4v

Stats Playlist:
English 7 Days Statistics Live Session :https://www.youtube.com/watch?v=11unm2hmvOQ&list=PLZoTAELRMXVMgtxAboeAx-D9qbnY94Yay
Hindi: Stats Playlist: https://www.youtube.com/watch?v=7y3XckjaVOw&list=PLTDARY42LDV6YHSRo669_uDDGmUEmQnDJ

Complete ML Playlist: https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe

Hindi: ML Playlist: https://www.youtube.com/watch?v=7uwa9aPbBRU&list=PLTDARY42LDV7WGmlzZtY-w9pemyPrKNUZ
5 DaysLive Deep Learning Playlist: https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns

Complete Deep Learning Playlist:
https://www.youtube.com/watch?v=YFNKnUhm_-s&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

What is log or logarithms? How log is used in data science and machine learning? In this video we will cover the whole point about log functions and how they are used in data science and machine learning. We will go over these topics

Check our Math and Statistics course for Data Science here : https://codebasics.io/courses/....math-and-statistics-

⭐️ Timestamps ⭐️
00:00 What exactly is log function?
02:33 Use of logarithms in real life
04:35 Use of logarithms in data science and machine learning

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CSV file can be downloaded here: https://github.com/codebasics/....math-for-machine-lea

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Math/Stats for Data science, ML playlist: https://www.youtube.com/playli....st?list=PLeo1K3hjS3u
Math/Stats for Data science, ML playlist Hindi:https://www.youtube.com/playli....st?list=PLPbgcxheSpE

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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

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👉Following topics are covered in this video:
00:00 - How to Learn Data Science
00:58 - What's Trending in Data Science?
05:03 - Prerequisites
06:42 - What about Certification programs?
10:00 - Prerequisites to become a Data Scientist
16:34 - Primary Skills
19:45 - What's Important?
20:55 - Data Scientist's Learning Path
24:31 - Data Scientist Job Descriptions
27:30 - Average Salary for a Data Scientist
28:47 - Who's Hiring?
30:18 - Final Thoughts

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Got any questions about Data Science career? Ask us in the comment section below.
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If you want to fast-track your career then you should strongly consider Data Science. The reason for this is that it is one of the fastest growing technology. There is a huge demand for Data Scientist. The salaries for Data Scientist is fantastic.There is a huge growth opportunity in this domain as well. Hence this Intellipaat Data Science project tutorial is your stepping stone to a successful career!
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This full-length interview will show you what a data science interview is like. This is a great video for anyone currently in the job-market for a data-focused role. It is also a solid video for anyone who wants a better understanding of the machine learning process. They cover topics that include building a dataset for training/testing purposes, feature vectorization, and model implementation details. Consider pausing after the question and thinking about how you would answer them.

Interviewer: @KeithGalli
Interviewee: @KylieYYing

⭐️ Contents ⭐️
⌨️ (0:00:00) Video overview & format
⌨️ (0:02:13) Introductory Behavioral questions
⌨️ (0:07:46) Social media platform bot issue task overview
⌨️ (0:15:26) What are some features we should investigate regarding the bot issue?
⌨️ (0:25:02) Classification model implementation details (using feature vectors)
⌨️ (0:41:38) What would a dataset to train models to detect bots look like? How would you approach collecting this data?
⌨️ (0:51:38) Technical implementation details (python libraries, cloud services, etc)
⌨️ (0:56:01) Any questions for me?
⌨️ (1:03:42) Post-interview breakdown & analysis

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Build your first AI project with Python! 🤖 This beginner-friendly machine learning tutorial uses real-world data.

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0:00:59 What is Machine Learning?
0:02:58 Machine Learning in Action
0:05:45 Libraries and Tools
0:10:40 Importing a Data Set
0:17:01 Jupyter Shortcuts
0:22:53 A Real Machine Learning Problem
0:26:09 Preparing the Data
0:29:15 Learning and Predicting
0:33:20 Calculating the Accuracy
0:39:41 Persisting Models
0:42:55 Visualizing a Decision Tree

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Notes of this Lecture:

What's the difference between Machine Learning and Data Science? - Almost every beginner who's about to get started with either Machine Learning or Data Science struggles with this fundamental concern most probably due to the reason that in both these technologies DATA plays a vital role.
In this video, we're going to see a clear picture of both the technologies and see all the differences between Data Science and Machine Learning in detail.

Check Out the Related Articles:

Difference Between Data Science and Machine Learning [https://www.geeksforgeeks.org/....difference-between-d
Machine Learning Tutorial [https://www.geeksforgeeks.org/machine-learning/]

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This video is contributed by Shivani Singh
LinkedIn profile of the contributor - https://www.linkedin.com/in/shivani-singh2019/

Please Like, Comment, and Share the Video among your friends.

#datascience #machinelearning #artificialintelligence #python #ml

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This Edureka video on "Data Science and Machine Learning for Non-programmers" is a part of the Data Science for Beginners Tutorial Series which is specifically dedicated to non-IT professionals who are trying to make a career in Data Science and Machine Learning in 2021 without the experience of working on programming languages. Here’s a list of topics that are covered in this Data Science for Beginners session:
00:00 Introduction to Data Science for Beginners Tutorial
01:20 Introduction to Data Science and Machine Learning
04:17 Data Science and Machine Learning Domains
08:11 Questions Every Non-Programmer Has
13:02 Data Science and Machine Learning Tools For Non-Programmers

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🔵Machine Learning Engineer Masters Program: https://bit.ly/3Hi1sXN

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🌕Post Graduate Diploma in Artificial Intelligence Course offered by E&ICT Academy
NIT Warangal: https://bit.ly/3qdRRdw

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#Edureka #DataScienceEdureka #MachineLearningEdureka #DataScience #Machinelearning #nonprogrammers #datasciencetutorialforbeginners
-------------------------------------

About the Data Science Masters Program

Data Science Masters Program makes you proficient in tools and systems used by Data Science Professionals. It includes training on Statistics, Data Science, Python, Apache Spark & Scala, Tensorflow and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe.

----------------------

Why Learn Data Science?

It’s been said that Data Scientist is the “Sexiest Job of the 21st century”. Why? Because over the past few years, companies have been storing their data. And this being done by each and every company, it has suddenly led to data explosion. Data has become the most abundant thing today. Data Science is also known as data driven science, which makes use of scientific methods, processes and systems to extract knowledge or insights from data in various forms, i.e either structured or unstructured.
-------------------------------------

Edureka's Data Science Masters Program Curriculum

🟠 Live Courses 🟠
Data Science Certification Course using R: https://www.edureka.co/data-sc....ience-r-programming-
Python Certification Training for Data Science: https://www.edureka.co/data-sc....ience-python-certifi
Apache Spark and Scala Certification Training: https://www.edureka.co/apache-....spark-scala-certific
Deep Learning with TensorFlow 2.0 Certification Training: https://www.edureka.co/ai-deep....-learning-with-tenso
Tableau Training and Certification: https://www.edureka.co/tableau....-certification-train


🟠 Self Paced Course 🟠
Python Statistics for Data Science Course
R Statistics for Data Science Course
--------------------------------------

Prerequisites

There are no prerequisites for enrollment to the Masters Program. However, as a goodwill gesture, Edureka offers a complimentary self-paced course in your LMS on SQL Essentials to brush up on your SQL Skills. This program is designed and developed for an aspirant planning to build a career in Machine Learning or an experienced professional working in the IT industry.

--------------------------------------

Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information

🔥 Data Science Training (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎") - https://www.edureka.co/data-sc....ience-r-programming-
This Machine Learning Algorithms Tutorial shall teach you what machine learning is, and the various ways in which you can use machine learning to solve a problem! Towards the end, you will learn how to prepare a data-set for model creation and validation and how you can create a model using any machine learning algorithm! In this Machine Learning Algorithms Tutorial video you will understand:

1) What is an Algorithm?
2) What is Machine Learning?
3) How is a problem solved using Machine Learning?
4) Types of Machine Learning
5) Machine Learning Algorithms
6) Demo


You can also check out this Machine Learning with Python video for more insights: https://youtu.be/nJKxWbQ1jaw

Check our complete Data Science playlist here: https://goo.gl/60NJJS

Subscribe to our channel to get video updates. Hit the subscribe button above.

#Edureka #MachineLearningAlgorithms #Datasciencetutorial #Datasciencecourse #datascience

How it Works?

1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

- - - - - - - - - - - - - -

About the Course

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

- - - - - - - - - - - - - -

Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

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Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

For more information, Please write back to us at sales@edureka.co or call us at IND: 9606058406 / US: 18338555775 (toll free).

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Customer Reviews:

Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "

Insights from Kaggle's annual survey focused on working data scientists.
Kaggle is the world's largest community of data scientists, and for the past 6 years the Kaggle Team has conducted a massive survey of machine learning practitioners. Fashioned after the renowned Stack Overflow Developer Survey, we ask questions about our data science and ML developer users' backgrounds, how they learn, which ML tools they’re using, details about their work life, and what they look forward to in the industry.

Speaker: Paul Mooney, PhD

Watch more:
All sessions from Google Cloud Next → https://goo.gle/next22-allsessions
Watch all the Design sessions → https://goo.gle/next22-design

Subscribe to Google Cloud Tech → https://goo.gle/GoogleCloudTech

The state of data science and machine learning in 2022 by Kaggle

DSN103

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Data Science and Machine Learning are both lucrative fields within artificial intelligence and tech. But which one is the best to learn? In this video I talk about exactly what is data science and machine learning and what is the difference between them.

What is Data Science:
Data Science is the process of making sense of data, often times larges amounts of data (also known as big data), and identifying meaningful patterns which are useful for making business decisions and can play a significant role in creating solutions to problems. It's used in a multitude of industries; finance and banking, transportation, health, etc.

What is Machine Learning:
Machine learning on the other hand, refers to the algorithms which machine learning engineers and even data scientists use in order to make a machine learn from data and apply the learning to new sets of data and get the answers we are looking for.

Where do they overlap:
Data science is not machine learning, but they do overlap, lots of data scientists make use of machine learning and vice versa. However, there are parts of machine learning that are completely unrelated to data science. A data scientist's job includes translating business questions into specific quantitative questions that can be answered with available data using statistical methodologies. In cases where questions cannot be answered with available data, they work with engineers to produce the required data.

Machine learning engineers design, implement and deliver ML components along with high quality software to solve complex problems. They also develop ML models using variety of ML design approaches as well as making use of knowledge such as data processing, regression, clustering, recommendations, classification, experimentation, model optimization.

-------------------------------------------------------------------------
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📌I'm Starting My Machine Learning Company (Day 1)
https://youtu.be/lh_wyUrjS9k

📌Top Machine Learning Certifications For 2021
https://youtu.be/YhXzUZGKhIY

📌Why You Should NOT Learn Machine Learning!
https://youtu.be/reY50t2hbuM

📌How I Learnt Machine Learning In 6 Steps (3 months)
https://youtu.be/OuC3wgp1Fnw

📌How To Learn Machine Learning For Free
https://youtu.be/QNKYKzTGerA
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Data Scientist Vs Machine Learning Engineer: Key Differences | Data Science | Machine Learning

In the IT industry, Data Scientists and Machine Learning Engineers work together in harmony toward a common outcome: to deploy ML models to help the business grow.

But, despite working for a shared goal, Data Scientists and Machine Learning Engineers require unique skills and are entrusted with different responsibilities to achieve that goal.

Here’s Abhishek, Senior Data Scientist at Microsoft, listing down the skills vital for both Data Scientists and Machine Learning Engineers.

Disclaimer: Opinions stated are exclusively mine and do not reflect the views or opinions of my employer.

#SCALER #datascience #machinelearning #faang #shorts

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►Data Science Projects:
https://www.youtube.com/watch?v=S_F_c9e2bz4&list=PLZoTAELRMXVPS-dOaVbAux22vzqdgoGhG&pp=iAQB

►Learn In One Tutorials

Statistics in 6 hours: https://www.youtube.com/watch?v=LZzq1zSL1bs&t=9522s&pp=ygUVa3Jpc2ggbmFpayBzdGF0aXN0aWNz

Machine Learning In 6 Hours: https://www.youtube.com/watch?v=JxgmHe2NyeY&t=4733s&pp=ygUba3Jpc2ggbmFpayBtYWNoaW5lIGxlYXJuaW5n

Deep Learning 5 hours : https://www.youtube.com/watch?v=d2kxUVwWWwU&t=1210s&pp=ygUYa3Jpc2ggbmFpayBkZWVwIGxlYXJuaW5n


►Learn In a Week Playlist

Statistics:https://www.youtube.com/watch?v=11unm2hmvOQ&list=PLZoTAELRMXVMgtxAboeAx-D9qbnY94Yay

Machine Learning : https://www.youtube.com/watch?v=z8sxaUw_f-M&list=PLZoTAELRMXVPjaAzURB77Kz0YXxj65tYz

Deep Learning:https://www.youtube.com/watch?v=8arGWdq_KL0&list=PLZoTAELRMXVPiyueAqA_eQnsycC_DSBns

NLP : https://www.youtube.com/watch?v=w3coRFpyddQ&list=PLZoTAELRMXVNNrHSKv36Lr3_156yCo6Nn

►Detailed Playlist:

Stats For Data Science In Hindi : https://www.youtube.com/watch?v=7y3XckjaVOw&list=PLTDARY42LDV6YHSRo669_uDDGmUEmQnDJ&pp=gAQB

Machine Learning In English : https://www.youtube.com/watch?v=bPrmA1SEN2k&list=PLZoTAELRMXVPBTrWtJkn3wWQxZkmTXGwe

Machine Learning In Hindi : https://www.youtube.com/watch?v=7uwa9aPbBRU&list=PLTDARY42LDV7WGmlzZtY-w9pemyPrKNUZ&pp=gAQB

Complete Deep Learning: https://www.youtube.com/watch?v=YFNKnUhm_-s&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi

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This Data Science with Python Tutorial will help you understand what is Data Science, basics of Python for data analysis, why learn Python, how to install Python, Python libraries for data analysis, exploratory analysis using Pandas, introduction to series and dataframe, loan prediction problem, data wrangling using Pandas, building a predictive model using Scikit-Learn and implementing logistic regression model using Python. The aim of this video is to provide a comprehensive knowledge to beginners who are new to Python for data analysis. This video provides a comprehensive overview of basic concepts that you need to learn to use Python for data analysis. Now, let us understand how Python is used in Data Science for data analysis.


This Data Science with Python tutorial will cover the following topics:
00:01:25 What is Data Science?
00:02:30 Why learn Python?
00:04:54 How to install Python?
00:06:48 Python libraries for data analysis
00:09:34 Exploratory analysis using SciPy
00:10:04 Exploratory analysis using NumPy
00:10:36 Exploratory analysis using Pandas
00:21:32 Data Wrangling Using Pands
00:30:22 Data Modelling with SciKiLearn
Introduction to series and dataframe
00:47:33 Loan prediction problem

To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

Download the Data Science career guide to explore and step into the exciting world of data, and follow the path towards your dream career: https://bit.ly/2S363Wx

You can also go through the slides here: https://goo.gl/ifQRpS

Read the full article here: https://www.simplilearn.com/career-in-data-science-ultimate-guide-article?utm_campaign=What-is-Data-Science-bTTxei-S1WI&utm_medium=Tutorials&utm_source=youtube

Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning

➡️ About Caltech Post Graduate Program In Data Science

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Caltech PG program in Data Science completion certificate
- Earn up to 14 CEUs from Caltech CTME
- Masterclasses delivered by distinguished Caltech faculty and IBM experts
- Caltech CTME Circle membership
- Online convocation by Caltech CTME Program Director
- IBM certificates for IBM courses
- Access to hackathons and Ask Me Anything sessions from IBM
- 25+ hands-on projects from the likes of Amazon, Walmart, Uber, and many more
- Seamless access to integrated labs
- Capstone projects in 3 domains
- Simplilearn’s Career Assistance to help you get noticed by top hiring companies
- 8X higher interaction in live online classes by industry experts

✅ Skills Covered
- Exploratory Data Analysis
- Descriptive Statistics
- Inferential Statistics
- Model Building and Fine Tuning
- Supervised and Unsupervised Learning
- Ensemble Learning
- Deep Learning
- Data Visualization

🔥Free Data Science Course: https://www.simplilearn.com/getting-started-data-science-with-python-skillup?utm_campaign=DataSciencewithPython&utm_medium=Description&utm_source=youtube

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🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

🔥 Data Scientist Masters Program (Use Code "𝐘𝐎𝐔𝐓𝐔𝐁𝐄𝟐𝟎"): https://www.edureka.co/masters....-program/data-scient
This Edureka video on "What is Data Science" will introduce you to the concepts of Data Science and how it is used to solve real-world problems. You will learn Data Science with an example on UBER dataset. Data science is the process of using the data to find solutions / to predict outcomes of a problem statement. Below are the topics covered in this Data Science Tutorial:

0:57 What is Data Science?
1:11 How Data Science works? : Data Science at UBER
2:06 Data Science Process
a. Business Requirements
b. Data Collection
c. Data Cleaning
d. Data Exploration and Analysis
e. Data Modelling
f. Data Validation
g. Deployment and Optimization
4:17 Data Science Applications
6:05 Who is a Data Scientist?
6:18 Data Scientist Job Trends
6:51 Data Scientist Skills

Subscribe to our channel to get video updates. Hit the subscribe button above.

Check our complete Data Science playlist here: https://goo.gl/60NJJS

Machine Learning Podcast: https://castbox.fm/channel/id1832236
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#edureka #DataScienceEdureka #whatisdatascience #Datasciencein8minutes #Datasciencecourse #datascience

- - - - - - - - - - - - - -

About the Master's Program

This program follows a set structure with 6 core courses and 8 electives spread across 26 weeks. It makes you an expert in key technologies related to Data Science. At the end of each core course, you will be working on a real-time project to gain hands on expertise. By the end of the program you will be ready for seasoned Data Science job roles.

- - - - - - - - - - - - - -

Topics Covered in the curriculum:

Topics covered but not limited to will be : Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Naïve Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop, Tableau Public, Data Visualization, Integration with R, Probability, Bayesian Inference, Regression Modelling etc.

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For more information, please write back to us at sales@edureka.co or call us at: IND: 9606058406 / US: 18338555775 (toll free)

In this video, I cover how to learn data science in 2022 (which tbh is the same as how I would learn data science in 2021still lol) - the minimize effort and maximize outcome way! If you're committed to learning data science in 2022, I have nothing more to say than to watch this video! I spend a lot of time putting this vid together and I can't wait for us to start ;)

📚Links mentioned in video
========================
Ken Jee's 66daysofdata:
https://www.youtube.com/watch?v=qV_AlRwhI3I
Ken Jee's How I would learn data science in 2021:
https://www.youtube.com/watch?v=41Clrh6nv1s&t=14s

Data Professor's Data science process:
https://www.youtube.com/watch?v=s4uF8UOJz9k&t=4s
https://www.youtube.com/watch?v=9hxuXzrCRz8

Krish Naik's Step by step action plan:
https://www.youtube.com/watch?v=lP1hb4BFAWA&t=618s

How I learned SQL from Scratch in 11 days:
https://www.youtube.com/watch?v=vaD3ZFFNwhM

🔗Affiliates
========================
365 Data Science:
https://bit.ly/3tIUBCY (link for 57% discount for their complete data science training)

Check out StrataScratch for data science interview prep:
https://stratascratch.com/?via=tina

Google Data Analytics Certificate on Coursera:
https://bit.ly/33tYQYA

🎥 My Filming Setup
========================
📷 camera: https://amzn.to/3LHbi7N
🎤 mic: https://amzn.to/3LqoFJb
🔭 tripod: https://amzn.to/3DkjGHe
💡 lights: https://amzn.to/3LmOhqk

⏰Timestamps
========================
00:00 Intro
01:15 Topics and framework
02:06 Programming
02:41 Stats
02:57 Visualization
03:13 EDA
03:47 Machine learning
05:34 The best way to learn
06:13 Apply framework to more topics
06:55 ACCOUNTABILITY
08:44 Resources/courses
10:48 How to choose projects
11:29 What I'm gonna do in 2021

📲Socials
========================
instagram: https://www.instagram.com/hellotinah/

linkedin: https://www.linkedin.com/in/tinaw-h/

discord: https://discord.gg/5mMAtprshX

🤯Study with Tina
========================
Study with Tina channel:
https://www.youtube.com/channe....l/UCI8JpGrDmtggrryhm

How to make a studying scoreboard:
https://www.youtube.com/watch?v=KAVw910mIrI

Scoreboard website:
scoreboardswithtina.com

livestreaming google calendar:
https://bit.ly/3wvPzHB

🎥Other videos you might be interested in
========================
How I consistently study with a full time job:
https://www.youtube.com/watch?v=INymz5VwLmk

How I would learn to code (if I could start over):
https://www.youtube.com/watch?v=MHPGeQD8TvI&t=84s

🐈‍⬛🐈‍⬛About me
========================
Hi, my name is Tina and I'm a data scientist at a FAANG company. I was pre-med studying pharmacology at the University of Toronto until I finally accepted that I would make a terrible doctor. I didn't know what to do with myself so I worked for a year as a research assistant for a bioinformatics lab where I learned how to code and became interested in data science. I then did a masters in computer science (MCIT) at the University of Pennsylvania before ending up at my current job in tech :)

📧Contact
========================
youtube: youtube comments are by far the best way to get a response from me!
linkedin: https://www.linkedin.com/in/tinaw-h/
email for business inquiries only: hellotinah@gmail.com

========================
Some links are affiliate links and I may receive a small portion of sales price at no cost to you. I really appreciate your support in helping improve this channel! :)

#DataScience #DataSciencein2021 #TinaHuang

🔥 Purdue Post Graduate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=DSvsML-DP0TKM0S2-8&utm_medium=Descriptionff&utm_source=youtube
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🔥AI Engineer Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=SCE-AIMasters&utm_medium=DescriptionFF&utm_source=youtube
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Data Science and Machine Learning are the two most buzzed terms in the industries these days. In this video, you will learn about data science vs. machine learning. We will first define the two terms and look at their relationship. Then, we'll see the different popular tools and applications used in data science and machine learning. Finally, you will get an idea about a data scientist and a machine learning engineer's skills and salary.

✅Subscribe to our Channel to learn more about the top Technologies: https://bit.ly/2VT4WtH

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#DataScienceVsMachineLearning #DataScienceAndMachineLearning #DataScience #DataScienceTutorial #MachineLearning#Simplilearn

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➡️ About Post Graduate Program In AI And Machine Learning

This AI ML course is designed to enhance your career in AI and ML by demystifying concepts like machine learning, deep learning, NLP, computer vision, reinforcement learning, and more. You'll also have access to 4 live sessions, led by industry experts, covering the latest advancements in AI such as generative modeling, ChatGPT, OpenAI, and chatbots.

✅ Key Features

- Post Graduate Program certificate and Alumni Association membership
- Exclusive hackathons and Ask me Anything sessions by IBM
- 3 Capstones and 25+ Projects with industry data sets from Twitter, Uber, Mercedes Benz, and many more
- Master Classes delivered by Purdue faculty and IBM experts
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Gain access to 4 live online sessions on latest AI trends such as ChatGPT, generative AI, explainable AI, and more
- Learn about the applications of ChatGPT, OpenAI, Dall-E, Midjourney & other prominent tools

✅ Skills Covered

- ChatGPT
- Generative AI
- Explainable AI
- Generative Modeling
- Statistics
- Python
- Supervised Learning
- Unsupervised Learning
- NLP
- Neural Networks
- Computer Vision
- And Many More…

👉 Learn More At: 🔥 Purdue Post Graduate Program In AI And Machine Learning: https://www.simplilearn.com/pgp-ai-machine-learning-certification-training-course?utm_campaign=DSvsML-DP0TKM0S2-8&utm_medium=Description&utm_source=youtube
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🔥AI Engineer Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/masters-in-artificial-intelligence?utm_campaign=SCE-AIMasters&utm_medium=DescriptionFF&utm_source=youtube
🔥AI & Machine Learning Bootcamp(US Only): https://www.simplilearn.com/ai-machine-learning-bootcamp?utm_campaign=DSvsML-DP0TKM0S2-8&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

One of the biggest challenges facing aspiring data scientists is consistency. If you are able to acquire incremental knowledge and skills in data science on a consistent basis, you’ll be amazed at how much knowledge you’ll accrue in a year or two.
Subscribe @krishnaikhindi channel for data science videos
#KrishNaik #datascience #consistent
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Statistics for Data Science by simplilearn is dedicated to help aspiring data scientists to understand the fundamentals of statistics and mathematics for data science. This data science tutorial for beginners by Simplilearn covers the Top 10 Statistics Concepts in Data Science and munch more

Statistics is a branch of applied mathematics, that is the study and manipulation of data, including ways to gather, review, analyze, and draw conclusions. This is why statistics still holds a very important place in today’s data science and business intelligence world. In this statistics tutorial, you will learn all about statistics, including, percentile in statistics, what is normal distribution, Central Limit Theorem, and probability density function. Start learning the statistics tutorial now.

00:00:00 Introduction to Statistics for Data Science
00:00:42 Statistical and Non-Statistical Analysis - Statistics for Data Science
00:01:25 Major Categories of Statistics For Data Science
00:04:11 Types of Statistical Measures - Statistics for Data Science
00:05:17 Statistical Terms - Statistics for Data Science
00:08:27 Hypothesis Testing - Statistics for Data Science
00:10:55 Variable Types - Statistics for Data Science
00:14:08 Parametric and Non-Parametric Tests - Statistics for Data Science
00:19:34 Advantages and Disadvantages of Non-Parametric Tests - Statistics for Data Science

#dataScience #StatisticsForDataScience #dataScienceTutorialForBeginners #statisticsAndMathematics #statistics #mathematics #2024 #simplilearn #ai #ML

➡️ About Caltech Post Graduate Program In Data Science
This post-graduation in Data Science leverages the superiority of Caltech's academic eminence. The Data Science program covers critical Data Science topics like Python programming, R programming, Machine Learning, Deep Learning, and Data Visualization tools through an interactive learning model with live sessions by global practitioners and practical labs.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Caltech PG program in Data Science completion certificate
- Earn up to 14 CEUs from Caltech CTME
- Masterclasses delivered by distinguished Caltech faculty and IBM experts
- Caltech CTME Circle membership
- Online convocation by Caltech CTME Program Director
- IBM certificates for IBM courses
- Access to hackathons and Ask Me Anything sessions from IBM
- 25+ hands-on projects from the likes of Amazon, Walmart, Uber, and many more
- Seamless access to integrated labs
- Capstone projects in 3 domains
- Simplilearn’s Career Assistance to help you get noticed by top hiring companies
- 8X higher interaction in live online classes by industry experts

✅ Skills Covered
- Exploratory Data Analysis
- Descriptive Statistics
- Inferential Statistics
- Model Building and Fine Tuning
- Supervised and Unsupervised Learning
- Ensemble Learning
- Deep Learning
- Data Visualization

🔥 Learn More: https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training?utm_campaign=StatisticsForDataScience&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

📲 Curious about a career in Data Analytics? Book a call with a program advisor: https://bit.ly/47LEBk3

Looking to get started in Data Analytics in 2024? This is the video for you! In it, we share what you need to know and the steps you need to take to successfully become a data analyst in 2024!

Hosted by our own senior data scientist, Tom Gadsby, this video will guide you through the steps and requirements needed to transform you from complete beginner into a job-ready data analyst within a realistic timeframe. Tom analyzes the current market and considers what he would do differently if he started over in the field in 2024.

Quick disclaimer: This won’t be an “easy” task, and in terms of time allocation, if you follow these steps, you can expect this journey to take up to a year to complete.

Let us know in the comments which steps you’re most excited by! Are there any you would add in based on your own career-change journey?

In this guide, we’ll cover the following key points:

(00:00) Intro
(00:44) Changes in The Industry
(02:11) How Tom Started in Data
(02:38) “Less Upfront Learning, More On-the-Fly Learning”
(03:30) “Try an Online School”
(05:16) Portfolio Projects
(06:11) Soft/Hard Skills
(06:46) Lean/Minimal Roadmap
(06:57) 1. Working With Data
(07:26) 2. Learning a Tool
(07:37) 3. Statistics
(07:58) 4. Visualization and Storytelling
(08:14) 5. Finding an Interesting Area
(08:34) How Long Does It Take to Become a Data Analyst?
(08:51) “Define Your Own Personal Roadmap”
(09:36) “Have More Confidence in Yourself”
(09:58) How Much Math is Needed in Data Analytics?
(10:28) “Get Comfortable With the Tools”
(11:05) “Take Advantage of Available Free Tools”
(11:30) “Study Other People’s Work”
(11:54) “Network”
(12:30) BONUS: Useful Resources to Learn Data Analytics
(12:36) Resource #1
(12:46) Resource #2
(12:56) Resource #3
(13:06) Resource #4
(13:24) Outro

Links & Resources featured in the video:

Medium: https://medium.com/
Kaggle: https://www.kaggle.com/
HackerRank: https://www.hackerrank.com/
CareerFoundry’s YouTube Channel: https://www.youtube.com/careerfoundry
Want to get a taste of Data Analytics? Start your journey with CareerFoundry’s free Data Analytics Short Course: https://bit.ly/DataShortCourse

Head over to CareerFoundry’s blog where you will find articles covering data analytics topics in much greater depth: https://bit.ly/DataAnalyticsBlog2

Thanks so much for watching!

#DataAnalytics #GetStartedInData #LearnDataAnalytics

Want more from CareerFoundry?

Check out our other social media channels and blog:
🔍 https://linktr.ee/CareerFoundry ​

For more information on our programs, visit us at:
🖥 https://careerfoundry.com/

How I Would Learn Data Analytics in 2024 (If I Had to Start Over)
https://youtu.be/f3FnCoKWmBg

🔥 Caltech Post Graduate Program In Data Science: https://www.simplilearn.com/post-graduate-program-data-science?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥IIT Kanpur Professional Certificate Course In Data Science (India Only): https://www.simplilearn.com/iitk-professional-certificate-course-data-science?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥 Data Science Bootcamp (US Only): https://www.simplilearn.com/post-graduate-program-data-science?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=DescriptionFirstFold&utm_source=youtube
🔥Data Scientist Masters Program (Discount Code - YTBE15): https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=DescriptionFirstFold&utm_source=youtube

This data science for beginners Tutorial will help you understand what is Data Science, who is a Data Scientist, what does a Data Scientist do and also how Python is used for Data Science. Data science is an interdisciplinary field of scientific methods, processes, algorithms and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining. This Data Science tutorial will help you establish your skills at analytical techniques using Python. With this Data Science video, you’ll learn the essential concepts of Data Science with Python programming and also understand how data acquisition, data preparation, data mining, model building & testing, data visualization is done. This Data Science tutorial is ideal for beginners who aspire to become a Data Scientist.

This Data Science tutorial will cover the following topics:
1. What is Data Science? ( 00:43 ) data science for beginners
2. Who is a Data Scientist? ( 02:02 ) data science for beginners
3. What does a Data Scientist do? ( 02:25 ) data science for beginners


To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/S....implilearn?sub_confi

You can also go through the slides here: https://goo.gl/V4Zn8i

Download the Data Science career guide to explore and step into the exciting world of data, and follow the path towards your dream career: https://www.simplilearn.com/data-science-career-guide-pdf?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=Description&utm_source=youtube

Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6

#datascienceforbeginners #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning

➡️ About Caltech Post Graduate Program In Data Science
This Post Graduation in Data Science leverages the superiority of Caltech's academic eminence. The Data Science program covers critical Data Science topics like Python programming, R programming, Machine Learning, Deep Learning, and Data Visualization tools through an interactive learning model with live sessions by global practitioners and practical labs.

✅ Key Features
- Simplilearn's JobAssist helps you get noticed by top hiring companies
- Caltech PG program in Data Science completion certificate
- Earn up to 14 CEUs from Caltech CTME
- Masterclasses delivered by distinguished Caltech faculty and IBM experts
- Caltech CTME Circle membership
- Online convocation by Caltech CTME Program Director
- IBM certificates for IBM courses
- Access to hackathons and Ask Me Anything sessions from IBM
- 25+ hands-on projects from the likes of Amazon, Walmart, Uber, and many more
- Seamless access to integrated labs
- Capstone projects in 3 domains
- Simplilearn’s Career Assistance to help you get noticed by top hiring companies
- 8X higher interaction in live online classes by industry experts

✅ Skills Covered
- Exploratory Data Analysis
- Descriptive Statistics
- Inferential Statistics
- Model Building and Fine Tuning
- Supervised and Unsupervised Learning
- Ensemble Learning
- Deep Learning
- Data Visualization

Learn more at: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=Description&utm_source=youtube

🔥Free Data Science Course: https://www.simplilearn.com/getting-started-data-science-with-python-skillup?utm_campaign=Data-Sciene-Tutorial-jNeUBWrrRsQ&utm_medium=Description&utm_source=youtube

🔥🔥 Interested in Attending Live Classes? Call Us: IN - 18002127688 / US - +18445327688

"

In this video, we will discuss if doing PHD in data science or machine learning is worth.

Do you want to learn technology from me? Check https://codebasics.io/ for my affordable video courses.

🌎 Website: https://www.codebasics.io/

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

Discover how to turn big data into even bigger results. For more info, visit: https://www.mygreatlearning.co....m/us/data-science/co

In this video, we will discuss is data science a good career by going over current job opportunities, and salaries and figuring out if given your current background, it makes sense to do data science.

Learn Data Science Using Free Resources: https://youtu.be/PFPt6PQNslE?si=OZA7ruWrJN9WFXq6
Can AI Replace Data Analyst Jobs: https://youtu.be/T8ryqTyVye4?si=X4U9gyx0HEZvhCwr
Career Transition Stories: https://www.youtube.com/playli....st?list=PLeo1K3hjS3u

⭐️ Timestamps ⭐️
00:00 Introduction
00:15 Job Opportunities and Future Growth
01:54 Salaries
02:42 Is it a Right Career for You?
05:54 Will AI Replace Data Science Jobs?

Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses.

Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.

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------

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🔗 Patreon: https://www.patreon.com/codeba....sics?fan_landing=tru

Are you in a high school and already dreaming about making a career in data science? In this video I will discuss some tips that you can start practicing while in school itself.

Do you want to learn technology from me? Check https://codebasics.io/ for my affordable video courses.

#datascience #codebasics #learndatascience #learn #school

🌎 Website: https://www.codebasics.io/

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

#️⃣ Social Media #️⃣
🔗 Discord: https://discord.gg/r42Kbuk
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❗❗ DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.

Interested in Data Science? Start with learning SQL to query data. You'll need it no matter which part of the data science pyramid you're interested in: https://joma.tech/sql





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Hello All in this video we will understand how we can learn Data Science Smartly

Please join as a member in my channel to get additional benefits like materials in Data Science, live streaming for Members and many more
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Here is a Quick roadmap in under 60 seconds to become a Data Scientist.

Many businesses see data science as the key to boosting their competitiveness. As a result, companies have enhanced their global brand positioning and earned consistent profitability, thanks in part to their dependence on data science.

Data scientists must have great verbal, written, and visual communication abilities because much of their job involves precise, rigorous, minutiae-driven analysis.

Having said that, to get into this field, one must have a thorough understanding of what steps they need to take. This is where most beginners usually get stuck.
Are you one of them?

Worry no more! Here is Abhishek, Senior Data Scientist at Microsoft, giving you a quick roadmap to go from a beginner to a Data Scientist.

What is Data Science?

Data Science is a mix of different tools, algorithms, and machine learning principles to discover hidden patterns in raw data. It still continues to evolve as a promising career path for various professionals. Data Scientists are able to identify relevant questions and collect data from various data sources, segregate the information and ultimately communicate the findings in a way that boosts businesses. A career in data science is both lucrative and rewarding.


Disclaimer: Opinions stated are exclusively mine and do not reflect the views or opinions of my employer.


#datascience #datascientist #FAANG #MAANG #SCALER

Explore analytics tools and solutions → https://ibm.biz/BdSPGc

Are you interested in data science? And have you heard of data analytics, but aren't sure how they're different? In this video, Martin Keen explains that while data science and data analytics are often used interchangeably, they have distinct roles. In terms of job roles, he covers the tools and practices of data scientists and contrast them with those of data analysts.

Get started for free on IBM Cloud → https://ibm.biz/sign-up-now

Subscribe to see more videos like this in the future → http://ibm.biz/subscribe-now

The only roadmap you need to learn data scientist skills in 6 months by spending 4 hours a day. No clickbait, no BS. Only real advice. The previous version of this roadmap has already helped many folks prepare for data scientist skills and get a job. I will discuss all the FREE learning resources, exact week-by-week study plans, assignments, and milestones. This also contains a free assignment tracker where you can track your weekly progress. We will also discuss resume and interview preparation for the data analyst job profile with a free resume and LinkedIn checklist.

To download the Roadmap PDF

1) Go to https://codebasics.io/resources
2) Click on the download button below the data science roadmap 2024 thumbnail
3) You need to create a login (takes 20 seconds) and then you will be able to download the roadmap PDF file

Direct link: https://codebasics.io/resources/data-science-roadmap-2024

Timestamp:
0:00 Intro
1:13 Research and Scam Protection
2:35 Python
5:22 Numpy, Panda, Data Visualization
10:05 Statistics and Math for Data Science
12:44 Exploratory Data Analysis (EDA)
14:54 SQL
18:24 Machine Learning
23:18 Deep Learning
25:24 NLP or Computer Vision

Do you want to learn technology from me? Check https://codebasics.io/?utm_source=description&utm_medium=yt&utm_campaign=description&utm_id=description for my affordable video courses.

Need help building software or data analytics/AI solutions? My company https://www.atliq.com/ can help. Click on the Contact button on that website.

🎥 Codebasics Hindi channel: https://www.youtube.com/channe....l/UCTmFBhuhMibVoSfYo

#️⃣ Social Media #️⃣

🧑‍🤝‍🧑 Discord for Community Support: https://discord.gg/r42Kbuk
📸 Codebasics' Instagram: https://www.instagram.com/codebasicshub/
📝 Codebasics' Linkedin : https://www.linkedin.com/company/codebasics/

------

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📝 Hem's Linkedin: https://www.linkedin.com/in/hemvad/

📽️ Hem's Instagram for daily tips: https://www.instagram.com/hemvadivel/
📸 Dhaval's Personal Instagram: https://www.instagram.com/dhavalsays/

🔗 Patreon: https://www.patreon.com/codeba....sics?fan_landing=tru

What is Data science?
Data science combines math and statistics, specialized programming, advanced analytics, artificial intelligence (AI), and machine learning with specific subject matter expertise to uncover actionable insights hidden in an organization’s data.

Workfiles: https://github.com/Talha-Train....ing/DATA-SCIENCE-TRA

Learn Data Science Free @ TalhaTraining to be a Data Scientist

Paid Course URL: https://talhatraining.com/cour....se/data-science-trai
Mobile & WhatsApp: +8801712742217
Email: training@talhatraining.com or talhatraining@gmail.com

Why learn data science?
Data science has the potential to improve the way we live and work, and it can empower others to make better decisions, solve problems, discover new advancements, and address some of the world's most pressing issues. With a data science career, you can be a part of this transformation.
1. Demand: Data Scientists are in High Demand.
2. Growth: Data Science Careers Have High Earning Potential.
3. Job Security: Data Science is a Fast-Growing Field.
4. Opportunity: Data Science Has a Range of Potential Job Opportunities.
5. Flexibility: Data Scientists are Needed in Various Sectors.

Who is called a data scientist?
A data scientist is a professional who creates programming code and combines it with statistical knowledge to create insights from data.

How to learn data Science?
The best way to learn data science is to work on projects so you can gain data science skills that can be applied immediately and are useful from a real-world implementation perspective. The sooner you start working on diverse data science projects, the faster you will learn the related concepts.
TalhaTraining teaches you the essential concepts of the Various Data Science Disciplines like Data, Big Data, BI, Traditional Data Science and ML.
Training Objectives
• Data Science - The Benefits
• Popular Data Science Techniques
• Popular Data Science Tools
• Careers in Data Science
• Debunking Common Misconceptions
• Probability
• Statistics
• Python Programming for Data Scientist
• Big Data and Spark with Python
• Advanced Statistical Methods
• Mathematics
• JavaScript for Data Scientist
• Deep Learning

#datascience #training #datasciencetraining #datasciencecourse #datasciencejobs #datascienceinternship #datascienceenthusiast #datascienceacademy #datasciencecommunity #datascienceskills #datascienceeducation #datascienceprojects #datascienceintern #datasciencecareer #datasciencecertification #datasciencecareers #datasciencelearning #datasciencewithpython #datasciencecareers #talhatraining

Becoming a Data Scientist requires mastering many different skills. In this video we will cover:
1. How to become a Data Scientist
2. How to learn Machine Learning with Python
3. How to learn Statistics for Data Science
4. The best Data Science courses
5. Complete Data Science roadmap

► FREE resources:
NOTE: You can audit the courses from Coursera to access them for free.
Full Disclosure: If you choose to pay for Coursera courses using our links, we get paid a small amount.
1. Data Science Math Skills by Duke University: https://imp.i384100.net/datasciencemathskills
2. Python For Data Visualization by IBM: https://imp.i384100.net/python....-for-data-visualizat
3. Applied Machine Learning in Python by University of Michigan: https://imp.i384100.net/applie....d-machine-learning-i
4. Machine Learning Specialization by Stanford University: imp.i384100.net/machine-learning-specialization
5. Learn Python: https://learnpython.org/
6. SQL W3 schools: https://www.w3schools.com/sql/
7. Business Metrics video: https://www.youtube.com/watch?v=JjA6hvmaK7I
8. Data Science Job Distribution: https://link.medium.com/QhRf8Ff2Nqb

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How big data starts to drive the world, and what kind of skills will you need to interpret it?

General Director of Alto Data Analytics, Jose Miguel Cansado, has developed his international career in IMB Watson and Alcatel-Lucent, including eight years in pacific Asia as Head of Multimedia and Mobile Communications. He is a telecommunication engineer and holds a master’s in marketing from INSEAD, as well as executive MBA from IE Business School.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

Learn Data Science is this full tutorial course for absolute beginners. Data science is considered the "sexiest job of the 21st century." You'll learn the important elements of data science. You'll be introduced to the principles, practices, and tools that make data science the powerful medium for critical insight in business and research. You'll have a solid foundation for future learning and applications in your work. With data science, you can do what you want to do, and do it better. This course covers the foundations of data science, data sourcing, coding, mathematics, and statistics.

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⭐️ Course Contents ⭐️
⌨️ Part 1: Data Science: An Introduction: Foundations of Data Science
- Welcome (1.1)
- Demand for Data Science (2.1)
- The Data Science Venn Diagram (2.2)
- The Data Science Pathway (2.3)
- Roles in Data Science (2.4)
- Teams in Data Science (2.5)
- Big Data (3.1)
- Coding (3.2)
- Statistics (3.3)
- Business Intelligence (3.4)
- Do No Harm (4.1)
- Methods Overview (5.1)
- Sourcing Overview (5.2)
- Coding Overview (5.3)
- Math Overview (5.4)
- Statistics Overview (5.5)
- Machine Learning Overview (5.6)
- Interpretability (6.1)
- Actionable Insights (6.2)
- Presentation Graphics (6.3)
- Reproducible Research (6.4)
- Next Steps (7.1)

⌨️ Part 2: Data Sourcing: Foundations of Data Science (1:39:46)
- Welcome (1.1)
- Metrics (2.1)
- Accuracy (2.2)
- Social Context of Measurement (2.3)
- Existing Data (3.1)
- APIs (3.2)
- Scraping (3.3)
- New Data (4.1)
- Interviews (4.2)
- Surveys (4.3)
- Card Sorting (4.4)
- Lab Experiments (4.5)
- A/B Testing (4.6)
- Next Steps (5.1)

⌨️ Part 3: Coding (2:32:42)
- Welcome (1.1)
- Spreadsheets (2.1)
- Tableau Public (2.2)
- SPSS (2.3)
- JASP (2.4)
- Other Software (2.5)
- HTML (3.1)
- XML (3.2)
- JSON (3.3)
- R (4.1)
- Python (4.2)
- SQL (4.3)
- C, C++, & Java (4.4)
- Bash (4.5)
- Regex (5.1)
- Next Steps (6.1)

⌨️ Part 4: Mathematics (4:01:09)
- Welcome (1.1)
- Elementary Algebra (2.1)
- Linear Algebra (2.2)
- Systems of Linear Equations (2.3)
- Calculus (2.4)
- Calculus & Optimization (2.5)
- Big O (3.1)
- Probability (3.2)

⌨️ Part 5: Statistics (4:44:03)
- Welcome (1.1)
- Exploration Overview (2.1)
- Exploratory Graphics (2.2)
- Exploratory Statistics (2.3)
- Descriptive Statistics (2.4)
- Inferential Statistics (3.1)
- Hypothesis Testing (3.2)
- Estimation (3.3)
- Estimators (4.1)
- Measures of Fit (4.2)
- Feature Selection (4.3)
- Problems in Modeling (4.4)
- Model Validation (4.5)
- DIY (4.6)
- Next Step (5.1)

--

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This Machine Learning Algorithms video will help you learn what is Machine Learning, various Machine Learning problems and algorithms, key Machine Learning algorithms with simple examples, and use cases implemented in Python. The key Machine Learning algorithms discussed in detail are Linear Regression, Logistic Regression, Decision Tree, Random Forest, and KNN algorithm.

Below topics are covered in this Machine Learning Algorithms Tutorial:
00:00 - 03:39 Machine Learning example and real-world applications
03:39 - 04:40 What is Machine Learning?
04:40 - 06:14 Processes involved in Machine Learning
06:14 - 09:40 Type of Machine Learning Algorithms
09:40 - 10:04 Popular Algorithms in Machine Learning
10:04 - 29:10 Linear regression
29:10 - 52:49 Logistic regression
52:49 - 01:04:45 Decision tree and Random forest
01:04:52 - 01:10:28 K nearest neighbor

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Data Science is the convergence of computer science, mathematics, and business expertise and helps entrepreneurs predict, diagnose, and solve their problems. Luv Aggarwal, a Data Solution Engineer at IBM, goes through the basics and explains how the discipline deploys data mining, data cleaning, machine learning and a variety of advanced analytics to yield actionable insights that will provide a roadmap for growth.

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Reality behind data science jobs. Is machine learning really cool?

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This Edureka Data Science Full Course video will help you understand and learn Data Science Algorithms in detail. This Data Science Tutorial is ideal for both beginners as well as professionals who want to master Data Science Algorithms. Below are the topics covered in this Data Science for Beginners course:
00:00 Data Science Full Course Agenda
2:44 Introduction to Data Science
9:55 Data Analysis at Walmart
13:20 What is Data Science?
14:39 Who is a Data Scientist?
16:50 Data Science Skill Set
21:51 Data Science Job Roles
26:58 Data Life Cycle
30:25 Statistics & Probability
34:31 Categories of Data
34:50 Qualitative Data
36:09 Quantitative Data
39:11 What is Statistics?
41:32 Basic Terminologies in Statistics
42:50 Sampling Techniques
45:31 Random Sampling
46:20 Systematic Sampling
46:50 Stratified Sampling
47:54 Types of Statistics
50:38 Descriptive Statistics
55:52 Measures of Spread
55:56 Range
56:44 Inter Quartile Range
58:58 Variance
59:36 Standard Deviation
1:14:25 Confusion Matrix
1:19:16 Probability
1:24:14 What is Probability?
1:27:13 Types of Events
1:27:58 Probability Distribution
1:28:15 Probability Density Function
1:30:02 Normal Distribution
1:30:51 Standard Deviation & Curve
1:31:19 Central Limit Theorem
1:33:12 Types of Probability
1:33:34 Marginal Probability
1:34:06 Joint Probability
1:34:58 Conditional Probability
1:35:56 Use-Case
1:39:46 Bayes Theorem
1:45:44 Inferential Statistics
1:56:40 Hypothesis Testing
2:00:34 Basics of Machine Learning
2:01:41 Need for Machine Learning
2:07:03 What is Machine Learning?
2:09:21 Machine Learning Definitions
2:11:48 Machine Learning Process
2:18:31 Supervised Learning Algorithm
2:19:54 What is Regression?
2:21:23 Linear vs Logistic Regression
2:33:51 Linear Regression
2:25:27 Where is Linear Regression used?
2:27:11 Understanding Linear Regression
2:37:00 What is R-Square?
2:46:35 Logistic Regression
2:51:22 Logistic Regression Curve
2:53:02 Logistic Regression Equation
2:56:21 Logistic Regression Use-Cases
2:58:23 Demo
3:00:57 Implement Logistic Regression
3:02:33 Import Libraries
3:05:28 Analyzing Data
3:11:52 Data Wrangling
3:23:54 Train & Test Data
3:20:44 Implement Logistic Regression
3:31:04 SUV Data Analysis
3:38:44 Decision Trees
3:39:50 What is Classification?
3:42:27 Types of Classification
3:42:27 Decision Tree
3:43:51 Random Forest
3:45:06 Naive Bayes
3:47:12 KNN
3:49:02 What is Decision Tree?
3:55:15 Decision Tree Terminologies
3:56:51 CART Algorithm
3:58:50 Entropy
4:00:15 What is Entropy?
4:23:52 Random Forest
4:27:29 Types of Classifier
4:31:17 Why Random Forest?
4:39:14 What is Random Forest?
4:51:26 How Random Forest Works?
4:51:36 Random Forest Algorithm
5:04:23 K Nearest Neighbour
5:05:33 What is KNN Algorithm?
5:08:50 KNN Algorithm Working
5:24:30 What is Naive Bayes?
5:25:13 Bayes Theorem
5:27:48 Bayes Theorem Proof
5:29:43 Naive Bayes Working
5:39:06 Types of Naive Bayes
5:53:37 Support Vector Machine
5:57:40 What is SVM?
5:59:46 How does SVM work?
6:03:00 Introduction to Non-Linear SVM
6:04:48 SVM Example
6:06:12 Unsupervised Learning Algorithms - KMeans
6:06:18 What is Unsupervised Learning?
6:06:45 Unsupervised Learning: Process Flow
6:07:17 What is Clustering?
6:09:15 Types of Clustering
6:10:15 K-Means Clustering
6:10:40 K-Means Algorithm Working
6:16:17 K-Means Algorithm
6:19:16 Fuzzy C-Means Clustering
6:21:22 Hierarchical Clustering
6:22:53 Association Clustering
6:24:57 Association Rule Mining
6:30:35 Apriori Algorithm
6:37:45 Apriori Demo
6:40:49 What is Reinforcement Learning?
6:42:48 Reinforcement Learning Process
6:51:10 Markov Decision Process
6:54:53 Understanding Q - Learning
7:13:12 Q-Learning Demo
7:25:34 The Bellman Equation
7:48:39 What is Deep Learning?
7:52:53 Why we need Artificial Neuron?
7:54:33 Perceptron Learning Algorithm
7:57:57 Activation Function
8:03:14 Single Layer Perceptron
8:04:04 What is Tensorflow?
8:07:25 Demo
8:21:03 What is a Computational Graph?
8:49:18 Limitations of Single Layer Perceptron
8:50:08 Multi-Layer Perceptron
8:51:24 What is Backpropagation?
8:52:26 Backpropagation Learning Algorithm
8:59:31 Multi-layer Perceptron Demo
9:01:23 Data Science Interview Questions

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