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Grokking Data Science
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Gain insights into data science with easy-to-follow, hands-on explanations. Explore essential concepts quickly and efficiently, even without prior statistics knowledge, for a career boost.

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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 to read to decide for yourself! - "I want to understand this data science concept. Let me Google it". Then after hours of surfing, reading random articles, and invoking the heavens, you are more confused than before. - "Data science is the sexiest and highest paying job of the 21st century. I want to become a data scientist too". - "I have a basic knowledge of Python, willingness to learn, and commitment to become a great data scientist." Is that you? If yes, you are at the right place.

Master the skills that can get you a $100K+ salary even if you bunked your statistics classes. No need to waste hours and hour...Show More

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

Learn Python fundamental libraries for data science

TAKEAWAY SKILLS

Python

Data Science

Machine Learning

NumPy

pandas

Content

59 Lessons5 Quizzes15 Challenges

Python Fundamentals for Data Science

25 Lessons

Step through Python basics, NumPy, Pandas, and foundational 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

12 Lessons

Discover the logic behind statistical analysis, probability concepts, distributions, and significance.

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

10 Lessons

Explore fundamental concepts, algorithms, model evaluation, and project execution in machine learning.

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

9 Lessons

Break down the steps to conduct an end-to-end machine learning project systematically.

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

3 Lessons

Map out the steps for achieving career success, overcoming imposter syndrome, and continuous growth.

How to Get That High-Paying Job

Imposter Syndrome

Final Thoughts

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Samia Khalid

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