Free Videos, Courses and Books

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 from data across a broad range of application domains. (From Wikipedia, https://en.wikipedia.org/wiki/Data_science).

Here are some tips for students who are struggling to learn Machine Learning:

• To start in the field, you need to know a few things: Mathematics, Statistics, Python Programming, and some other miscellaneous tools. 

• Take advantage of online resources, like those listed below. Since this is a collection from various sources, the videos/articles may not appear coherent. But that is the cost of free tutorials!

• Find a mentor. A mentor can provide you with guidance and support. A mentor can help you understand the material, troubleshoot problems, and find resources.

• Join a study group. Studying with other students can help you stay motivated and learn from each other.

The minimum needed to get into our MPS in Data Science Program 

• • Calculus 1 - Khan Academy - https://www.khanacademy.org/math/calculus-1 

• If you are not ready for Calculus 1, start with Precalculus - https://www.khanacademy.org/math/precalculus 

• • Statistics and probability - https://www.khanacademy.org/math/statistics-probability 

• If you are not ready for that much statistics, perhaps start with High school statistics, https://www.khanacademy.org/math/probability 

• • Learn Python with Jupyter https://learnpythonwithjupyter.com/ 

Mathematics

• • Linear Algebra Review by Andrew Ng (~1 hour), https://www.youtube.com/watch?v=4Pm-htIGVMQ 

  • Calculus 1 - Full College Course (~12 hours), https://www.youtube.com/watch?v=HfACrKJ_Y2w 

Statistics

• Statistics - A Full University Course on Data Science Basics (~ 8 hours video), https://www.youtube.com/watch?v=xxpc-HPKN28 

• OR

• Statistics for Data Science (~7 hours), https://www.youtube.com/watch?v=Vfo5le26IhY&t=5s 

Python Programming

• • Python for Beginners - Learn Python in 1 Hour (Using PyCharm), https://www.youtube.com/watch?v=kqtD5dpn9C8 

  • Data Analysis with Python and Jupyter Notebooks (including Pandas etc), https://www.youtube.com/watch?v=e5O7jlR9zaU 

  • Python NumPy Tutorial for Beginners, https://www.youtube.com/watch?v=QUT1VHiLmmI 

  • Complete Python Pandas Data Science Tutorial, https://www.youtube.com/watch?v=vmEHCJofslg 

  • Python Object Oriented Programming (OOP) - For Beginners, https://www.youtube.com/watch?v=JeznW_7DlB0 

  • How to Do Data Cleaning (step-by-step tutorial on real-life dataset), https://www.youtube.com/watch?v=qxpKCBV60U4 

  • Grouping and Aggregating - Analyzing and Exploring Your Data, https://www.youtube.com/watch?v=txMdrV1Ut64 

  • Python Data Visualization Tutorial, https://www.youtube.com/watch?v=Nt84_TzRkbo 

Broad Introduction to Data Science

• • Intro to Data Science - Crash Course for Beginners (~2 hours), https://www.youtube.com/watch?v=N6BghzuFLIg 

Introductory Machine Learning

• • Linear Regression vs Logistic Regression | Machine learning Algorithms Explained, https://www.youtube.com/watch?v=QWYkQDvCo4Y 

  • Feature Selection in Python, https://www.youtube.com/watch?v=iJ5c-XoHPFo 

Data Ethics

• • Introduction to Data Ethics, https://www.youtube.com/watch?v=qVo9oApl4Rs 

Artificial Intelligence from Basics to Advanced

The following list compiled by Aman Chadha, https://www.linkedin.com/feed/update/urn:li:activity:7053241114551566336/ 

Here is his list of courses along with their respective YouTube playlists (note that this is an ordered list of increasing difficulty, based on Aman's personal experience). Check out his watch list with all of the above pointers (and a much larger list of such resources and more): https://aman.ai/watch

Stanford University

• CS221 - Artificial Intelligence: Principles and Techniques by Percy Liang and Dorsa Sadigh: https://lnkd.in/grECwbD4

• CS229 - Machine Learning by Andrew Ng: https://lnkd.in/gY8a2yZN

• CS230 - Deep Learning by Andrew Ng: https://lnkd.in/gTk-gKPm

• CS231n - Convolutional Neural Networks for Visual Recognition by Fei-Fei Li and Andrej Karpathy: https://lnkd.in/gGUMZH_G

• CS224n - Natural Language Processing with Deep Learning by Christopher Manning: https://lnkd.in/giWDZGVX

• CS234 - Reinforcement Learning by Emma Brunskill: https://lnkd.in/gwZKQ-28

• CS330 - Deep Multi-task and Meta Learning by Chelsea Finn: https://lnkd.in/gvVr_Y4M

• CS25 - Transformers United: https://lnkd.in/gEtKgHGC

Carnegie Mellon University

• CS/LTI 11-711: Advanced NLP by Graham Neubig: https://lnkd.in/gSt29ZVt

• CS/LTI 11-747: Neural Networks for NLP by Graham Neubig: https://lnkd.in/gRRrY8uq

• CS/LTI 11-737: Multilingual NLP by Graham Neubig: https://lnkd.in/g8QkaTfy

• CS/LTI 11-777: Multimodal Machine Learning by Louis-Philippe Morency: https://lnkd.in/gKFJDbU4

• CS/LTI 11-785: Introduction to Deep Learning by Bhiksha Raj and Rita Singh: https://lnkd.in/gVp96GdB

• CS/LTI Low Resource NLP Bootcamp 2020 by Graham Neubig: https://lnkd.in/grYqa3YZ

Massachusetts Institute of Technology

• 6.S191 - Introduction to Deep Learning by Alexander Amini and Ava Amini: https://lnkd.in/gWMUpMQg

• 6.S094 - Deep Learning by Lex Fridman: https://lnkd.in/gcDgqbH6

• 6.S192 - Deep Learning for Art, Aesthetics, and Creativity by Ali Jahanian: https://lnkd.in/gEyRbEZx

University College London

• COMP M050 Reinforcement Learning by David Silver: https://lnkd.in/gEpkWmqh

His full Read List, https://aman.ai/read/ 

Hiss full Watch List, https://aman.ai/watch/ 

Appendices

A: Recommended Software for Python

You will be learning Python programming in this course and you need a development environment (IDE) for that purpose.  Here are a few choices, in decreasing order of importance for this course:

• If you are into Data Science, the best tool is Anaconda | The World's Most Popular Data Science Platform 

• Or its smaller version, Miniconda — Conda documentation (See appendix 1 for details)

• JupyterLab is the latest web-based interactive development environment for notebooks, code, and data Project Jupyter | Home 

B: Miniconda and Jupyter

Installing Miniconda and Jupyter Notebook

First, download and install Miniconda from: https://docs.conda.io/en/main/miniconda.html 

Once installed in (C:\Users\maliyou1\Miniconda3), run 'Miniconda Powershell' from the Start Menu (Under Anaconda3 (64-bit) folder).

and then install the classic Jupyter Notebook from within Miniconda Powershell with:

(base) PS C:\> pip install notebook

To run the notebook: 

(base) PS C:\> jupyter notebook

The web browser will open in C: 

You will need to change to the correct directory /Users/maliyou1/OneDrive/0 TurningPoint Healthcare Solutions/Python Scripts (Copy)/

C: Google Colab

Another easy option to practice Python is to use the free Google Colaboratory. It is pre-set for us and requires practically no setup. If you have a gmail account, you can start using it immediately. https://colab.research.google.com/ 

D: Docker 

Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers. The service has both free and premium tiers. The software that hosts the containers is called Docker Engine.  Installing and running docker requires multiple steps and is not exactly a menu-driven system. Hence you need to watch a few videos on the subject. Here is a good one:

[1] Docker Tutorial for Beginners, https://www.youtube.com/watch?v=pTFZFxd4hOI 

[2] List of Docker Commands: Cheat Sheet, https://phoenixnap.com/kb/list-of-docker-commands-cheat-sheet 

E: Further Reading

• Youtube Python Tutorials

• Python for Beginners - Video Tutorials

• Python Data Science Handbook by Jake VanderPlas. O’Reilly Media, Available online (free) via https://jakevdp.github.io/PythonDataScienceHandbook/ 

• A video tutorial series for statistics fundamentals

• Machine Learning Course, Lecture 1 - Andrew Ng (Autumn 2018), https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU 

F: Other External Courses

This is a random collection of courses and tools - not necessarily free. 

Chromebook Data Science

• Chromebook Data Science (CBDS) is a free, massive open online educational program offered through Leanpub to help anyone who can read, write, and use a computer to move into data science, the number one rated job. 

Coursera

• Machine Learning by Stanford University (by Andrew NG, 10 weeks long)

• Mathematics for Machine Learning and Data Science Specialization (Offered by DeepLearning.AI), https://www.coursera.org/specializations/mathematics-for-machine-learning-and-data-science 

• Coursera / JHU Data Science Specialization (10+ courses), https://www.coursera.org/specializations/jhu-data-science 

Google:

• Machine Learning Crash Course, https://developers.google.com/machine-learning/crash-course/ 

• Machine Learning Crash Course (Newer version), https://learndigital.withgoogle.com/digitalunlocked/course/machine-learning-crash-course 

EdX

• Data Science courses at EdX, https://www.edx.org/course/subject/data-science 

Udemy

• The Data Science Course 2023: Complete Data Science Bootcamp, https://www.udemy.com/the-data-science-course-complete-data-science-bootcamp/  

• Deep Learning with The Tensorflow and Python Masterclass,  https://www.udemy.com/course/deep-learning-with-the-tensorflow-and-python-masterclass/learn/lecture/15536430#overview 

Udacity

• Become a Data Scientist, https://www.udacity.com/course/data-scientist-nanodegree--nd025 

• The School of Data Science, https://www.udacity.com/school-of-data-science 

HarvardX

• Professional Certificate in Data Science,  https://pll.harvard.edu/series/professional-certificate-data-science 

YouTube

• Data Science Full Course - Learn Data Science (~10 Hours, by Edureka), https://www.youtube.com/watch?v=-ETQ97mXXF0 

• Machine Learning — Andrew Ng, Stanford University, https://www.youtube.com/playlist?list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN 

• Machine Learning In-Depth Tutorial 2022 (~10 hours), https://www.youtube.com/watch?v=pYpFvmOx9_U 

• 20 ML YouTube Courses, https://github.com/dair-ai/ML-YouTube-Courses/blob/main/README.md#deep-learning-cs-182 

eduCBA

• EDUCBA All in One Data Science Bundle Certification Bundle, https://www.educba.com/data-science/ 

FAST

• Practical Deep Learning for Coders, https://course.fast.ai/

DataCamp

•  https://www.datacamp.com/ 

DeepLearning.AI (NOT free)

• Natural Language Processing Specialization, https://www.deeplearning.ai/courses/natural-language-processing-specialization/ 

G. Tech Guides

• Data Scientist, https://techguide.org/careers/data-scientist/

• Data Analyst, https://techguide.org/careers/data-analyst/

• Other similar careers, https://techguide.org/careers/

H. Free Comic Books!

What is AI, Learning from Data, Whol lives who dies who decides, all about that bias, we are AI:

https://dataresponsibly.github.io/we-are-ai/comics/ 

I. Cloud-Based Data Science

Cloud Based Data Science (CBDS) is a free online educational tool to help anyone who can read, write, and use a computer to move into data science, the number one rated job. It is a sequence of 11 MOOCs offered by faculty members in the Johns Hopkins Department of Biostatistics, Bloomberg School of Public Health.

The following 11 courses are included in this track...

Introduction to DataTrail, Google and the Cloud, Organizing Data Science Projects, Version Control, Introduction to R, Data Tidying, Data Visualization, Getting Data, Data Analysis, Written and Oral Communication in Data Science, Getting a Job in Data Science

https://leanpub.com/universities/set/jhu/cloud-based-data-science 

J. Data Science - Weekly Topics (Alternate list)

• Week 1 – Course overview and introduction to data science and Python

  • Intro to Data Science - Crash Course for Beginners, https://www.youtube.com/watch?v=N6BghzuFLIg 

• Week 2 – Basic python programming

  • Python for Beginners - Learn Python in 1 Hour (Using PyCharm), https://www.youtube.com/watch?v=kqtD5dpn9C8 

  • Data Analysis with Python and Jupyter Notebooks (but including Pandas etc), https://www.youtube.com/watch?v=e5O7jlR9zaU 

• Week 3 – Introduction to Numpy

  • Python NumPy Tutorial for Beginners, https://www.youtube.com/watch?v=QUT1VHiLmmI 

• Week 4 – Introduction to Pandas and data-frames

  • Complete Python Pandas Data Science Tutorial, https://www.youtube.com/watch?v=vmEHCJofslg 

• Week 5 – Object-oriented programming and automation

  • Python Object Oriented Programming (OOP) - For Beginners, https://www.youtube.com/watch?v=JeznW_7DlB0 

• Week 6 – Data loading, cleaning, summarization

  • How to Do Data Cleaning (step-by-step tutorial on real-life dataset), https://www.youtube.com/watch?v=qxpKCBV60U4 

• Week 7 – Data aggregation and transformation

  • Grouping and Aggregating - Analyzing and Exploring Your Data, https://www.youtube.com/watch?v=txMdrV1Ut64 

• Week 8 – Data visualization

  • Python Data Visualization Tutorial, https://www.youtube.com/watch?v=Nt84_TzRkbo 

• Week 9 – Review of basics statistics

  • Statistics For Data Science, https://www.youtube.com/watch?v=Lv0xcdeXaGU 

• Week 10 – Statistical and exploratory data analysis and outlier detection

  • Exploratory Data Analysis (EDA) Using Python, https://www.youtube.com/watch?v=-o3AxdVcUtQ 

• Week 11 – Linear Algebra Review

  • Linear Algebra review by Andrew Ng, https://www.youtube.com/watch?v=4Pm-htIGVMQ 

• Week 12 – Linear and Logistic Regression

  • Linear Regression vs Logistic Regression | Machine learning Algorithms Explained, https://www.youtube.com/watch?v=QWYkQDvCo4Y 

• Week 13 – Feature Selection

  • Feature Selection in Python, https://www.youtube.com/watch?v=iJ5c-XoHPFo 

• Week 14 – Data Ethics

  • Introduction to Data Ethics, https://www.youtube.com/watch?v=qVo9oApl4Rs 

K. AI in the Urdu Language

• Fundamentals of Python (23 videos by Dr. Shahid Qamar), https://www.youtube.com/playlist?list=PLzTwljMDC2vysjHLr4_EJhbyCiy7BYslK 

• Foundation of Artificial Intelligence in Urdu (14 videos by Dr. Shahid Qamar), https://www.youtube.com/playlist?list=PLzTwljMDC2vw_najv2N7s_Ey_XXtNnu1k 

• Machine Learning Models (49 videos by Dr. Shahid Qamar), https://www.youtube.com/playlist?list=PLzTwljMDC2vxii9s2Nr_fehMBoWXTtjpu 

• Deep Learning Fundamentals (17 videos by Dr. Shahid Qamar), https://www.youtube.com/playlist?list=PLzTwljMDC2vwm_e2lVqFZCXyGbT3ixPf6 

• Deep Learning- Hands-On (33 videos by Dr. Shahid Qamar), https://www.youtube.com/playlist?list=PLzTwljMDC2vziiuUSgSzhxqxoiI2JuB2r 

• 
  

• Python 3 Tutorial in Urdu | Hindi - Complete Course in 2019 (52 videos),  https://www.youtube.com/playlist?list=PLWZm9ufk1fmroyT0ogrWeyrfYc5qgD5f3 

• Artificial Intelligence Complete Course in Urdu/Hindi (17 videos by SigmaWonderz), https://www.youtube.com/playlist?list=PLEuj8cszMzGVsL9DiCMcTY82_HLrJ2MBW 

• Many playlists on topics including PowerBI, Python, Stats, and Maths (Saima Academy), https://www.youtube.com/@saimaacademy5537/playlists. 

Free Books