Grokking Data Science - AI-Powered Learning for Developers

This data science course for beginners teaches everything you need to know about data science and contains common data science interview questions.

Beginner

59 Lessons

10h

Certificate of Completion

This data science course for beginners teaches everything you need to know about data science and contains common data science interview questions.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

56 Playgrounds

15 Challenges

5 Quizzes

This course includes

56 Playgrounds

15 Challenges

5 Quizzes

Course Overview

Master the skills that can get you a $100K+ salary even if you bunked your statistics classes. No need to waste hours and hours on browsing from one article to the next and piecing together the info you need to grasp important topics. No need to get overwhelmed by the information overload. Find easy to follow, hands-on, and fun explanations of all the essential topics in one place so you can quickly and efficiently learn what you need to thrive as a data scientist. "Is this course right for me?" Continue...Show More

TAKEAWAY SKILLS

Python

Data Science

Machine Learning

Numpy

Pandas

What You'll Learn

Learn Python fundamental libraries for data science

Learn statistics fundamentals for data science

Learn machine learning fundamentals for data science

Solve an end-to-end machine learning project

Get to know how to get the highest paying data scientist job

What You'll Learn

Learn Python fundamental libraries for data science

Course Content

Python Fundamentals for Data Science

In this chapter, you will discover how to use Python tools such as Jupyter, NumPy, and Pandas for data science, and explore data visualization techniques.

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

This chapter explores the basics of statistics, covering probability distributions, statistical significance, and Bayesian inference for data analysis.

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

In this chapter, you'll learn the fundamentals of machine learning, including types, algorithms, key models, metrics, and essential concepts.

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

In this chapter, you will explore managing an end-to-end machine learning project, from data analysis and preprocessing to model tuning and system maintenance.

Introduction 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 Assignment Further Study Material

The Real Talk

In this chapter, you’ll learn how to land a high-paying Data Scientist job, tackle Imposter Syndrome, and get tips for your career journey.

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

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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AI-Powered Mock Interviews

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Adaptive Learning

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AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!