# 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.

**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

## Linear Algebra

1. Instructor: Grant Sanderson / Channel: 3Blue1Brown

Course: Essence of Linear Algebra

2. Instructor: Prof. Gilbert Strang / MIT OpenCourseWare

Course: Linear Algebra / Youtube

3. Instructor: Kaare Brandt Petersen & Michael Syskind Pedersen

Book: Matrix Algebra

## Calculus

1. Instructor: Grant Sanderson / Channel: 3Blue1Brown

Course: Essence of Calculus

2. Instructor: Prof. David Jerison / MIT OpenCourseWare

Course: Single Variable Calculus / YouTube

3. Instructor: Prof. Denis Auroux / MIT OpenCourseWare

Course: Multi Variable Calculus / YouTube

## Probability & Statistics

1. Instructor: Khan Academy

Course: Probability

2. Instructor: Khan Academy

Course: Statistics

3. Instructor: Joshua Starmer

Course: Statistics Fundamentals

4. Instructor: Prof. John Tsitsiklis / MIT OpenCourseWare

Course: Probabilistic Methods

5. Instructor: Allen B. Downey

Book: Think Stats

**Note: Use this book after completing the fundamentals of python & statistics**

## Convex Optimization (Advanced Concept)

1. Instructor: Prof. Stephen Boyd / Stanford

# 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

# Machine Learning

## Beginner Courses

- Instructor: Prof. Andrew Ng
- Instructor: Prof. Abu Yaser Mustafa
- Instructor: Krish Naik
- AI Introduction: deeplearning.ai / Edureka
- Artificial Intelligence by MIT: Course

## Applied Machine Learning Course with Python

## Books for Hands on Machine Learning

# Deep Learning

## Specialization Courses

- Instructor: Prof. Andrew Ng / YouTube
- Instructor: Krish Naik
- Instructor: Yann Le’Cun
- Instructor: MIT

## 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

# 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 Administrator-Associate Training: Course

# Model Deployment

- Instructor: Krish Naik
- Instructor: Daniel Bourke
- Live End-to-End Model Deployment: Tutorial
- Model Deployment using Amazon Sagemaker: Tutorial
- Model Deployment using Azure: Tutorial

# 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

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.