100 days : Your Data Science and ML Degree

Everything you need to know — Part 1…

Welcome back peeps. Hope all’s well at your end. While I’m extremely busy with work; I target to write once every three days if my schedule allows. This post is a 100 days — your Data Science and ML degree ( Part 1) — mega compilation of Data Science and ML theory and projects that we have built till now and progressing forward — what to expect.

System Design Case Studies — In Depth

Design Instagram

Design Messenger App

Complete Data Structures and Algorithm Series

Complexity Analysis

Backtracking

Sliding Window

Greedy Technique

Two pointer Technique

Arrays

Linked List

Strings

Stack

Queues

1- D Dynamic Programming

Divide and Conquer Technique

Recursion

Github —

You can use this as a starting point to advanced level and devise your own Data Science and ML degree ( PS: you don’t have to buy expensive courses to be able to learn/get into/ build data science and ML).

Some of the other best Series —

30 Days of Natural Language Processing ( NLP) Series

How to solve any System Design Question ( approach that you can take)?

30 days of Data Engineering with projects Series

60 days of Data Science and ML Series with projects

100 days : Your Data Science and Machine Learning Degree Series with projects

23 Data Science Techniques You Should Know

Tech Interview Series — Curated List of coding questions

Complete System Design with most popular Questions Series

Complete Data Visualization and Pre-processing Series with projects

Complete Python Series with Projects

Complete Advanced Python Series with Projects

Kaggle Best Notebooks that will teach you the most

Complete Developers Guide to Git

All the Data Science and Machine Learning Resources

210 Machine Learning Projects

30 days of Machine Learning Ops

Projects Videos —

All the projects, data structures, SQL, algorithms, system design, Data Science and ML , Data Analytics, Data Engineering, , Implemented Data Science and ML projects, Implemented Data Engineering Projects, Implemented Deep Learning Projects, Implemented Machine Learning Ops Projects, Implemented Time Series Analysis and Forecasting Projects, Implemented Applied Machine Learning Projects, Implemented Tensorflow and Keras Projects, Implemented PyTorch Projects, Implemented Scikit Learn Projects, Implemented Big Data Projects, Implemented Cloud Machine Learning Projects, Implemented Neural Networks Projects, Implemented OpenCV Projects,Complete ML Research Papers Summarized, Implemented Data Analytics projects, Implemented Data Visualization Projects, Implemented Data Mining Projects, Implemented Natural Leaning Processing Projects, MLOps and Deep Learning, Applied Machine Learning with Projects Series, PyTorch with Projects Series, Tensorflow and Keras with Projects Series, Scikit Learn Series with Projects, Time Series Analysis and Forecasting with Projects Series, ML System Design Case Studies Series videos will be published on our youtube channel ( just launched).

Subscribe today!

Tech Newsletter —

If you are interested, you can join my newsletter through which I send tech interview tips, techniques, patterns, hacks — Software Development, ML, Data Science, Startups and Technology projects to more than 30K readers. You can subscribe to Tech Brew :

Start from here —

Day 1–15 : Python

Complete Python with projects —

Complete Advanced Python with Projects — Mega Compilation Part 6

Python Crash Course — Part 1

Python Crash Course — Part 2

Efficient Code and Optimization techniques for Python

Highly Recommended Data Science and Machine Learning Courses that you MUST take ( with certificate) —

Complete Data Scientist

Complete Data Analyst

Complete Data Engineering

Complete Machine Learning Engineer

Complete Deep Learning

Complete Natural Language Processing

Complete Self Driving Car Engineer

Find best data science and data engineering courses here

Find best Machine Learning and Deep Learning courses here

Day 16–30 : Data pre-processing and Data Visualization

Complete Data Preprocessing and Data Visualization with Projects — Mega Compilation Part 2

How To Choose Right Data Visualization Charts For Your Data?

Day 31–60 : Data Science and Machine Learning

Part 1 —

Part 2 —

Part 3 —

Part 4 —

Part 5 —

Combined —

Day 1 — Day 60 : Quick Recap of 60 days of Data Science and ML

Day 61–71 : Natural Language Processing

Day 1–30 Days of Natural Language Processing Series with Projects

Quick Recap : 30 days of Natural Language Processing ( NLP) with Projects Series

Day 72–100 : Build Projects

Data visualization and Clustering

Data visualization and Clustering

Cluster Analysis using Python — Part 1

Detailed Analysis of the Netflix Content

Detailed Crypto Analysis

Hyperparameter Tuning with Keras Tuner

Analyzing Video using Python, OpenCV and NumPy

ANN, Linear Regression, Decision Tree Regression and Random Forest with a project

Principal Component Analysis with a project

Bidirectional Encoder Representations from Transformers ( BERT) with a project

Build Machine Learning Pipelines( With Code)

Recurrent Neural Network with Keras

Custom Layers in Keras

Clustering Geolocation Data in Python using DBSCAN and K-Means

Facial Expression Recognition using Keras

Implement Tokenization, POS tagging, Chunking, Named Entities Recognition ( NER)

Part 2 : Coming soon!

All the Complete System Design Series Parts —

1. System design basics

2. Horizontal and vertical scaling

3. Load balancing and Message queues

4. High level design and low level design, Consistent Hashing, Monolithic and Microservices architecture

5. Caching, Indexing, Proxies

6. Networking, How Browsers work, Content Network Delivery ( CDN)

7. Database Sharding, CAP Theorem, Database schema Design

8. Concurrency, API, Components + OOP + Abstraction

9. Estimation and Planning, Performance

10. Map Reduce, Patterns and Microservices

11. SQL vs NoSQL and Cloud

12. Most Popular System Design Questions

Github —

Happy learning and keep coding :)

Some of the links are affiliates.

Follow for more updates, stay tuned and of-course let me end this post with a quote by Steve Jobs ;)

“Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do. If you haven’t found it yet, keep looking. Don’t settle. As with all matters of the heart, you’ll know when you find it.”