This repository contains everything you need to become proficient in Data Analytics
- Business Understanding
Data Driven Decision
How to formulate solutions to business problems?
Descriptive Analysis
Predictive Analysis
Diagnostic Analysis
Prescriptive Analysis
- Data Analytics Ecosystem
Data Life Cycle
Data Analysis complete process — step by step
- Probability
Basic Probability
Advanced Probability
- Statistics
Must know Statistics topics
- Basic SQL
Must know SQL basics
- Advanced SQL
Must know Advanced SQL
- Data Collection
Web scraping
- Data Cleaning
Python
Pandas
Numpy
- Data Manipulation
Join
Melt
Cut
Transform
Clean
Slicing
Reshaping
Filter
Group by
Pivot and Merge
Concatenate
MultiIndexing
Stacking
Hierarchical indexing
Aggregate
Summarize data
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Data Calculations
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Data Aggregations
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Data Visualization
Data Visualization basics
Which chart to choose and when?
Data Visualization using Matplotlib and Seaborn
Data Visualization using Plotly and Folium
Data Visualization using Bokeh
- Tableau
Tableau Basics
Create trend lines and understand the relevant statistical metrics such as p-value and R-squared
Create forecasts, Barcharts, Area Charts, Box and Whisker
Create Histogram, Bullet Chart, Bubbles Chart, Funnel Charts, Advanced Charts
Create Scatterplots , Piecharts, Treemaps
Create Maps — Detailed Maps, Symbol Maps, Density Maps
Create Advanced Maps
Create Interactive Dashboards
Create Storylines
Work with Data Blending in Tableau
Create Table Calculations
Create Dual Axis Charts
Create Calculated Fields
Create Visualizations using Calculated Fields
Tableau String Functions
Tableau Date Functions
Tableau Type Conversion
Tableau Reporting
Implement Aggregation, Granularity, and Level of Detail
Create and use Groups
Create and add Filters and Quick Filters
Create Reference Lines with Parameters
Implement Clustering
Implement Filters, including the context filter
Implement Grouping & Sets
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Data Preparation
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Data Modeling
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Data Evaluation
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Statistical Analysis
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Regression analysis
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Least squares and inference
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Regression models
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Big Data Analytics
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Classification Trees
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Projects
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
6 Highly Recommended Data Science and Machine Learning Courses that you MUST take ( with certificate) -
- Complete Data Scientist : https://bit.ly/3wiIo8u
Learn to run data pipelines, design experiments , build recommendation systems, and deploy solutions to the cloud.
- 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
- 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.
- 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.
- 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.
- Complete Deep Learning: https://bit.ly/3T5ppIo
Learn to implement Neural Networks using the deep learning framework PyTorch