How do I start?

This is by far the question that I get asked the most.

This article gives you a path forward. It’s a simple and streamlined roadmap. At the end you should be like,

A short disclaimer

Building a career in machine learning is a lifelong pursuit.
But every journey starts with the first step, and this is where these resources come in.

As a disclaimer, I have an engineering background. I’m not a researcher, so I’m not qualified to advise those who aspire to work in academia. I can tell, however, what’s useful in the industry, so this list is biased towards that goal.

Our aim is to become a Full-Stack Data Scientist by 2023.

Everything starts with Python

Learning Python is not just a prerequisite for getting into Machine Learning or Data Science, but it’s an investment that will help your career.

To start with, we'll focus all of our energy on learning the language.

Learning Objectives

✅ Learn fundamentals of Python programming.
✅ Learn to write cleaner code in Python with Object-Oriented Programming.
✅ Enhance your problem-solving skills using data structures and algorithms in Python.
✅ Master advanced concepts including modules, processes, unit tests, web-related tasks.
✅ Learn to extract, represent, and process data using Numpy, Pandas, and Dask and use Matplotlib for data visualization.

Path Contents

Module 1: Python Fundamentals

Starting with the fundamentals of programming with Python.

• Intro and Installation
• Data Types and Variables
• Operators
• Conditional Statements
• Functions
• Loops

Module 2: OOP

Shift gear to Object-Oriented Programming in Python.

• Classes and Objects
• Information hiding
• Inheritance
• Polymorphism
• Object relationships

Module 3: Data Structures

Learn how to implement data structures in your next project.

• Built-in Data Structures
• Arrays
• Stacks, Queues, and Deques
• Linked Lists
• Trees
• Maps, Hash Tables
• Data Structures for Graphs

Module 4: Algorithms

Learn how to implement algorithms in your next project.

• Time and Space Complexity
• Sorting and Selection
• Recursion
• Tree Traversal Algorithm
• Search Trees
• Graph Algorithms
• Text Processing

Module 5: Advanced Python

Take your Python skills to the next level with advanced concepts.

• Arguments Parsing
• Error Handling
• Context Managers
• Iterators and Generators
• Functional Programming
• Modules
• Regular Expressions
• Processes and Threads
• Multiprocessing and Parallel Processing
• Serialization
• Unit Testing and Profiling
• Web Scraping and Web APIs
• Flask
• Packaging Python Libraries

Module 6: Data Analysis

Gain the ability to make sense out of data using powerful tools and techniques.

• Statistics Concepts
• SQL
• Dive into Numpy
• Processing Data using Pandas and Dask
• Working with Files
• Data Visualizations

Next Step

I would recommend you to subscribe to the newsletter and receive new lessons straight to your inbox.

These modules will be released weekly.

Take them in order, one at a time, and be patient. This is a marathon, not a sprint.

Exciting News Coming up. Stay tuned!!!!