Last Updated: 8/26/2023
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.
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/
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 - 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 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
Intro to Data Science - Crash Course for Beginners (~2 hours), https://www.youtube.com/watch?v=N6BghzuFLIg
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
Introduction to Data Ethics, https://www.youtube.com/watch?v=qVo9oApl4Rs
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
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
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/
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
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)/
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/
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
Python Data Science Handbook by Jake VanderPlas. O’Reilly Media, Available online (free) via https://jakevdp.github.io/PythonDataScienceHandbook/
Machine Learning Course, Lecture 1 - Andrew Ng (Autumn 2018), https://www.youtube.com/watch?v=jGwO_UgTS7I&list=PLoROMvodv4rMiGQp3WXShtMGgzqpfVfbU
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
DeepLearning.AI (NOT free)
Natural Language Processing Specialization, https://www.deeplearning.ai/courses/natural-language-processing-specialization/
Data Scientist, https://techguide.org/careers/data-scientist/
Data Analyst, https://techguide.org/careers/data-analyst/
Other similar careers, https://techguide.org/careers/
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/
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
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
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.