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Python Fundamentals for Data Science

Creating the Workspace - Jupyter Notebooks Python Libraries Learning NumPy - An Introduction NumPy Basics - Creating NumPy Arrays and Array Attributes NumPy Basics - Array Indexing and Slicing NumPy Basics - Reshaping and Concatenation NumPy Arithmetic and Statistics - Computations and Aggregations NumPy Arithmetic and Statistics - Comparison and Boolean Masks Exercises: NumPy Learning Pandas - An Introduction Pandas Core Components - The Series Object Pandas Core Components - The DataFrame Object Pandas DataFrame Operations - Read, View and Extract Information Pandas DataFrame Operations - Selection, Slicing, and Filtering Pandas DataFrame Operations - Grouping and Sorting Pandas DataFrame Operations - Dealing With Missing and Duplicates Pandas DataFrame Operations - Pivot Tables and Functions Pandas: Further Readings and Cheat Sheet Exercises: Pandas Data Visualization - An Introduction Data Visualization - Matplotlib Tips Data Visualization Techniques - Scatter, Line, and Histogram Data Visualization Techniques - Bar and Box Plot Data Visualization Cheat Sheet Quiz: Data Visualization

The Fundamentals of Statistics

Introduction Statistical Features - Basics Statistical Features - Working With Box Plots Basics of Probability Bayesian Statistics Probability Distributions - An Introduction Types of Distributions - Uniform, Bernoulli, and Binomial Types of Distributions - Normal Types of Distributions - Poisson and Exponential Probability Distributions Recap Statistical Significance Quiz: Statistics

Machine Learning 101

Introduction Understanding Machine Learning Types of Machine Learning Algorithms Machine Learning Algorithms I Machine Learning Algorithms II Quiz: Machine Learning Algorithms Evaluating a Model Quiz: Evaluating a Model Key Points to Remember Machine Learning Project Checklist

End-to-End Machine Learning Project

Kaggle Challenge - Exploratory Data Analysis

Kaggle Challenge - Data Preprocessing

Kaggle Challenge - Data Transformation

Kaggle Challenge - Machine Learning Models

Kaggle Challenge - Fine Tune Parameters

Kaggle Challenge - Present, Launch and Maintain the System

Further Study Material

The Real Talk

How to Get That High-Paying Job Imposter Syndrome Final Thoughts

Grokking Data Science/

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Further Study Material

Further Study Material

We'll cover the following...

Data science is a vast field. There is always more to learn and explore. Especially, if you start browsing and looking for resources around the Internet, it won’t take long before you get information overload. The key is to not become overwhelmed.

Choose one or two courses or books at a time. Read, learn, understand, and apply the concepts before ...