Path to Full Stack Data Science

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Path to Full Stack Data Science
Online Resources for Beginners
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 of online resources, books and tutorials; and for beginners, its overwhelming to say the least. Most of the time beginners start with either a python course or a machine learning course or some basic mathematics course. But many a times, a big number of them do not know where to start from. 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.
Figure: 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 End-to-End Data Science domain. It will help the 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 in-depth online courses and tutorials available out there for domains comprising full stack 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 are Provided for the Following Segments
Mathematics — Linear Algebra, Calculus, Probability, Statistics & Convex Optimization
Python Programming — Fundamentals, OOP Concepts, Algorithms, Data Structures & Data Science Applications
R Programming — Fundamentals, Data Science & Web Applications
Core DS Concepts — Database Programming, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Data Visualization, Model Deployment & Big Data
C/C++ Programming — Fundamentals, Problem Solving, OOP Concepts, Algorithms & Data Structures
Computer Science Fundamentals — Introduction, Algorithms, Data Structures, Discrete Mathematics, Operating System, Computer Architecture, Database Concepts, Git & Github
Mathematics
Applied Deep Learning with Python & TensorFlow
Deep Learning A-Z: Hands-On Artificial Neural Networks: Course
TensorFlow Complete Course by freecodecamp.org: Course
DeepLearning.AI TensorFlow Developer Professional Certificate: Course
TensorFlow Data & Deployment: Course
Books for Hands on Deep Learning
Deep Learning Book: Book
Fundamentals of Deep Learning: Book
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
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 have tried to provide specific resources (courses/tutorials/books) which are in depth, prominent on the web and have proved to be quite beneficial to a large number of learners in the data science arena. I have tried to be as specific as possible and listed those which I have familiarity with. It goes without saying, 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 the beginners. I will finish off by providing some of the topmost YouTube channels which have tons of learning materials and some pretty good guidance in regards to the subject matter.
Top YouTube Channels for Data Science