Path to Full Stack Data Science
Start your journey toward mastering all aspects of the field of Data Science with this focused list of indepth selflearning resources. Curated with the beginner in mind, these recommendations will help you learn efficiently, and can also offer existing professionals useful highlights for review or help filling in any gaps in skills.
By Jawwad Shadman Siddique, Graduate Researcher at Texas Tech.
Full Stack Data Science has become one of the hottest industries in the field of computer science. Starting from traditional mathematics to advance concepts like data engineering, this industry demands a breadth of knowledge and expertise. Its demand has seen an exponential rise in online resources, books, and tutorials. For beginners, it's overwhelming, to say the least. Most of the time, beginners start with either a python course, a machine learning course, or some basic mathematics course. But many times, a large number of them do not know where to start. And with so many resources to go to, many of them keep scraping through resources. Moving between Udemy, edX, Coursera, and YouTube, many hours are lost.
Subject Matters involved with Data Science.
The goal of this article is not to list out the required syllabus but rather list out some of the prominent online resources for each subject area in the endtoend Data Science domain. It will help beginners start their data science journey without wasting their precious time. I have tried to put down the resources in as much order as possible. But it might vary to a great extent depending upon the individual’s expertise and requirements. The focus of this article is solely the listing out of some of the thorough and indepth online courses and tutorials available out there for domains comprising fullstack data science. I have tried to keep the list as short as possible so that it helps the starters get started with their learning without much selection.
Resources for the following areas
 Mathematics — Linear Algebra, Calculus, Probability, Statistics, and Convex Optimization
 Python Programming — Fundamentals, OOP Concepts, Algorithms, Data Structures, and Data Science Applications
 R Programming — Fundamentals, Data Science, and Web Applications
 Core DS Concepts — Database Programming, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Data Visualization, Model Deployment, and Big Data
 C/C++ Programming — Fundamentals, Problem Solving, OOP Concepts, Algorithms, and Data Structures
 Computer Science Fundamentals — Introduction, Algorithms, Data Structures, Discrete Mathematics, Operating System, Computer Architecture, Database Concepts, Git, and GitHub
Mathematics
Linear Algebra
 Instructor: Grant Sanderson / Channel: 3Blue1Brown
Course: Essence of Linear Algebra  Instructor: Prof. Gilbert Strang / MIT OpenCourseWare
Course: Linear Algebra / Youtube  Instructor: Kaare Brandt Petersen & Michael Syskind Pedersen
Book: Matrix Algebra
Calculus
 Instructor: Grant Sanderson / Channel: 3Blue1Brown
Course: Essence of Calculus  Instructor: Prof. David Jerison / MIT OpenCourseWare
Course: Single Variable Calculus / YouTube  Instructor: Prof. Denis Auroux / MIT OpenCourseWare
Course: MultiVariable Calculus / YouTube
Probability & Statistics
 Instructor: Khan Academy
Course: Probability  Instructor: Khan Academy
Course: Statistics  Instructor: Joshua Starmer
Course: Statistics Fundamentals  Instructor: Prof. John Tsitsiklis / MIT OpenCourseWare
Course: Probabilistic Methods  Instructor: Allen B. Downey
Book: Think Stats
Note: Use this book after completing the fundamentals of python and statistics
Convex Optimization (Advanced Concept)
 Instructor: Prof. Stephen Boyd / Stanford
Course: Introduction to Convex Optimization
Python Programming
Python Fundamentals
 Python For Everybody: Course/ Book / Web
 Learn Python The Hard Way: Book
 Think Python: Book
 Python Programming by Krish Naik: Course
 Complete Python Bootcamp: Course
Algorithms & OOP with Python
 Problem Solving & OOP with Python: Course
 Grokking Algorithms: Book
 Automate the Boring Stuff with Python: Course
 (Advanced) Social Network Analysis for Startups: Book
Data Science with Python
 Python Data Science Handbook: Book
 Python for Data Science: freecodecamp course
 Introduction to Computational Thinking & Data Science: Course
 Applied Data Science with Python: Course
R Programming
 R for Data Science: Book
 Handson Machine Learning with R: Book
 Interactive Web Apps using R Shiny: Tutorial
Database Programming
 Fundamentals of Database Systems: Book
 SQL vs NoSQL MySQL vs MongoDB: Tutorial/ Tutorial
 Full Database Design Course: Tutorial
 SQL using MySQL: Course
 PostgreSQL: Course
 PostgreSQL for Everybody: Course
 SQLite with Python: Course
 Popular Database: Tutorial
Data Visualization
 Power BI Full Course by Edureka: Course
 Power BI Full Course by Simplilearn: Course
 Tableau Full Course by Edureka: Course
 Tableau Full Course by Simplilearn: Course
 Tableau Crash Course by freecodecamp.org: Course
Machine Learning
Beginner Courses
 Instructor: Andrew Ng
 Instructor: Abu Yaser Mustafa
 Instructor: Krish Naik
 AI Introduction: ai/ Edureka
 Artificial Intelligence by MIT: Course
Applied Machine Learning Course with Python
Books for Handson Machine Learning
 Handson Machine Learning with ScikitLearn, Keras & TensorFlow: Book
 The 100 Page ML Book: Book
 Learning from Data: Book
Deep Learning
Specialization Courses
 Instructor: Andrew Ng/ YouTube
 Instructor: Krish Naik
 Instructor: Yann Le’Cun
 Instructor: MIT
Applied Deep Learning with Python & TensorFlow
 Deep Learning AZ: HandsOn Artificial Neural Networks: Course
 TensorFlow Complete Course by freecodecamp.org: Course
 AI TensorFlow Developer Professional Certificate: Course
 TensorFlow Data & Deployment: Course
Books for Handson Deep Learning
Natural Language Processing
 NLP Specialization by deeplearning.ai: Course
 NLP with Deep Learning by Stanford: Course/ YouTube
 Complete NLP by Krish Naik: Course
Computer Vision
 Convolutional Neural Networks for Visual Recognition: Course
 Complete CV by Krish Naik: Course
 Full OpenCV by freecodecamp.org: Course
Reinforcement Learning
 Reinforcement Learning by DeepMind: Course
 Reinforcement Learning by Stanford: Course
 Reinforcement Learning by University of Alberta: Course
Web Development
 Django Tutorial by Corey Schafer: Course
 Django for Everybody: Course
 Flask Tutorial by Corey Schafer: Course
 Web Development by Traversy Media: Web Link/ YouTube
 Full Stack Web Development Guide: Tutorial
 Web Design for Everybody: Course
 Web Applications for Everybody: Course
Git & Github
 Crash course by freecodecamp.org: Course
 Crash course by Traversy Media: Course
 Full Course by Edureka: Course
 Git Tutorial for Beginners by Mosh: Course
 Git and Github tutorial by Amigoscode: Course
AWS
 AWS Certifications: Tutorial
 AWS Tutorial for Beginners: Course
 AWS Basics for Beginners: Course
 AWS Certified Cloud Practitioner Training: Course
 AWS Certified Solutions Architect — Associate Training: Course
 AWS Certified Developer — Associate Training: Course
 AWS SysOps AdministratorAssociate Training: Course
Model Deployment
 Instructor: Krish Naik
 Instructor: Daniel Bourke
 Live EndtoEnd Model Deployment: Tutorial
 Model Deployment using Amazon Sagemaker: Tutorial
 Model Deployment using Azure: Tutorial
Big Data
 Introduction to Big Data by CrashCourse: Tutorial
 Introduction to Big Data by Edureka: Tutorial
 Big Data Intro by Simplilearn: Tutorial
 Big Data & Hadoop by Edureka: Course
 Apache Spark by Edureka: Course
C/C++ Programming for Problem Solving
Tutorials & Courses
 Full C Tutorial by Mike: Course
 Full C++ Tutorial by Caleb Curry: Course
 Full C++ Tutorial by Suldina Nurak: Course
 C++ OOPS Concepts: Course
 Problem Solving & OOP using C++: Course
 Pointers in C++: Course
 STL using C++: Course
 Data Structure using C/C++: Course
Books
 The C++ Programming Language by Bjarne Stroustrup: Book
 The C Programming Language by Dennis Ritchie: Book
Algorithms & Data Structure
 Introduction to Algorithms by MIT: Course
 Design & Analysis of Algorithms by MIT: Course
 Advanced Algorithms by MIT: Course
 Competitive Programming Guide by GeeksforGeeks: Web Link
 Introduction to Algorithms by Thomas H. Cormen: Book
Fundamentals of Computer Science
 Missing Semester of Computer Science: Course
 Computer System Architecture by CMU: Course
 Computer System Architecture by MIT: Course
 Operating System by Neso Academy: Course
 Operating System by UC Berkely: Course
 Basics of Software Engineering: Course
I tried to provide specific resources (courses/tutorials/books) that are indepth, prominent on the web, and have proved to be quite beneficial to a large number of learners in the data science arena. I tried to be as specific as possible and listed those with which I have familiarity. It goes without saying that many great resources have also been left out. As such, this list should not be considered an expert guide by any means. Rather, it picks out some of the highlighted courses to make the learning journey easier for beginners. I will finish off by providing some of the topmost YouTube channels that have tons of learning materials and some pretty good guidance in regards to the subject matter.
Top YouTube Channels for Data Science
 Krish Naik
 Sentdex
 3Blue1Brown
 org
 StatQuest with Joshua Starmer
 Python Programmer
 Corey Schafer
 Tech with Tim
 Two Minute Papers
 Data School
 Caleb Curry
 Andreas Kretz
 Traversy Media
 Stanford Online
 Yannic Kilcher
 GeeksforGeeks
 Numberphile
 AI
 mycodeschool
 Art of Visualization
Original. Reposted with permission.
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