This repository contains everything you need to become proficient in Data Analytics

Complete Cheat Sheet for Tech Interviews - How to prepare efficiently

I took theses Projects Based Courses to Build Industry aligned Data Science and ML skills

Part 1 - How to solve Any ML System Design Problem

Start here : Day1 of Data Analytics Series

Day 1 : Data Analytics basics and kickstart of Data analytics with projects series

Day 2: Business Understanding — Data Driven Decision Making, Descriptive Analysis, Predictive Analysis, Diagnostic Analysis, Prescriptive Analysis

Day 3 : Data Analytics Ecosystem — Data Life Cycle, Data Analysis complete process ( most important things)

Day 4 : Probability, Conditional Probability, Binomial Distribution, Probability Density Function, Sampling Distribution

Day 5 : Statistics

Day 6 : Basic and Advanced SQL

Day 7 : Data Collection, Data Cleaning and Python

Day 8 : Pandas and Numpy

Day 9 : Data Manipulation

Day 10 : Data Visualization — Part 1

Day 11 : Project 1 : Data Visualization — Part 2

Day 12 : Data Visualization — Part 3

Day 13: Tableau — Part 1

Day 14: Tableau — Part 2

Day 15: Tableau — Part 3

Day 16 : Data Analysis Project 2

Day 17 : Data Analysis Project 3

Day 18: Data Analysis Project 4

Day 19: Data Analysis Project 5

Day 20 : Data Analysis Project 6 — Part 1

Categorical and Numerical Features

Missing Value Analysis

Fill the missing Values

Unique Value Analysis

Univariate Analysis

Bivariate Analysis

Multivariate Analysis

Correlation Analysis

Day 21 : Data Analysis Project 7

Data Profiling

Feature Engineering

GroupBy Features

Categorical and Numerical Features

Missing Value Analysis

Fill the missing Values

Unique Value Analysis

Univariate Analysis

Bivariate Analysis

Multivariate Analysis

Correlation Analysis

Day 22 : Data analysis Project 8

Linear Regression

Data Profiling

Feature Engineering

Sort Values

Categorical and Numerical Features

Missing Value Analysis

Unique Value Analysis

Univariate Analysis

Bivariate Analysis

Multivariate Analysis

Correlation Analysis

Correlation Coefficients

Day 23: Data Analytics Project 9

Linear Regression

Data Profiling

Correlation Coefficients

Spearman’s ρ

Pearson’s r

Kendall’s τ

Cramér’s V (φc)

Phik (φk)

Day 24: Data Analytics Project 10

Standardization

Encoding

Linear Regression

Data Profiling

Categorical and Numerical Features

Missing Value Analysis

Unique Value Analysis

Univariate Analysis

Bivariate Analysis

Multivariate Analysis

Day 25: Data Analytics Project 11

Summary Functions

Indexing

Grouping

Sorting

Data Profiling

Categorical and Numerical Features

Missing Value Analysis

Unique Value Analysis

Data Visualization

Correlation Coefficients

Day 26: Power BI

Day 27: Performance Metrics

Day 28: Regression

Linear Regression

Multi Linear Regression

Polynomial Regression

Day 29: Regression

Support Vector Regression

Decision Tree Regression

Random Forest Regression

Day 30: Classification

Naive Bayes

Random Forest

Missing Value Analysis

Unique Value Analysis

Take Complete Hands On Tableau Course : Link

Complete 60 Days of Data Science and Machine Learning Series

30 days of Machine Learning Ops

30 Days of Natural Language Processing ( NLP) Series

Data Science and Machine Learning Research ( papers) Simplified **

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

Exceptional Github Repos — Part 1

Exceptional Github Repos — Part 2

All the Data Science and Machine Learning Resources

210 Machine Learning Projects

1. Complete Data Scientist : https://bit.ly/3wiIo8u

Learn to run data pipelines, design experiments , build recommendation systems, and deploy solutions to the cloud.

2. Complete Data Engineering : https://bit.ly/3A9oVs5

Learn to design data models, build data warehouses and data lakes, automate data pipelines, and work with massive datasets

3. Complete Machine Learning Engineer : https://bit.ly/3Tir8ub

Learn advanced machine learning techniques and algorithms - including how to package and deploy your models to a production environment.

4. Complete Data Product Manager : https://bit.ly/3QGUtwi

Leverage data to build products that deliver the right experiences, to the right users, at the right time. Lead the development of data-driven products that position businesses to win in their market.

5. Complete Natural Language Processing : https://bit.ly/3T7J8qY

Build models on real data, and get hands-on experience with sentiment analysis, machine translation, and more.

6. Complete Deep Learning: https://bit.ly/3T5ppIo

Learn to implement Neural Networks using the deep learning framework PyTorch