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Introduction to Data Science and scikit-learn in Python
  • Level Foundation
  • Duration 14 hours
  • Course by LearnQuest
  • Offered by

About

This course will teach you how to leverage the power of Python and artificial intelligence to create and test hypothesis. We'll start for the ground up, learning some basic Python for data science before diving into some of its richer applications to test our created hypothesis. We'll learn some of the most important libraries for exploratory data analysis (EDA) and machine learning such as Numpy, Pandas, and Sci-kit learn. After learning some of the theory (and math) behind linear regression, we'll go through and full pipeline of reading data, cleaning it, and applying a regression model to estimate the progression of diabetes. By the end of the course, you'll apply a classification model to predict the presence/absence of heart disease from a patient's health data.

Modules

Welcome to the Course

    • 1 Videos
    • 1 Discussion
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1 Discussions

  • Welcome to the Course!

1 Videos

  • Course Introduction

Introduction to Jupyter and Variables

    • 3 Videos
    • 2 Readings
    • 1 Lab
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1 Labs

  • The Playground

3 Videos

  • Module Introduction
  • Python and Jupyter Notebook Basics
  • Setting Up the Environment

2 Readings

  • A Note on Coding Alongside the Videos
  • Jupyter Notebook Basics

Data Structures for Data Science

    • 2 Videos
    • 2 Readings
    • 2 Lab
    • 2 Programming
    • 1 Assignment
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2 Programming

  • Lists
  • Dictionaries

1 Assignment

  • Practice Quiz: Data Structures

2 Labs

  • Programming Assignment Solutions: Lists
  • Programming Assignment Solutions: Dictionaries

2 Videos

  • Lists
  • Dictionaries

2 Readings

  • Python Docs: Data Structures
  • List Comprehensions

Loops and Functions

    • 2 Videos
    • 1 Readings
    • 2 Lab
    • 2 Programming
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2 Programming

  • Loops and List Comprehensions
  • Functions

2 Labs

  • Programming Assignment Solutions: Loops and List Comprehensions
  • Programming Assignment Solutions: Functions

2 Videos

  • Loops
  • Functions

1 Readings

  • Keyword Arguments

Importing Libraries

    • 1 Videos
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1 Videos

  • Libraries and Modules

Quiz

    • 1 Assignment
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1 Assignment

  • Introduction to Python

Numpy, Pandas, and Scikit-Learn

    • 3 Videos
    • 1 Readings
    • 1 Discussion
    • 1 Assignment
Show info about module content

1 Assignment

  • Practice Quiz: Numpy Basics

1 Discussions

  • Case Study: First Image of a Black Hole

3 Videos

  • Module Introduction
  • Deep Dive into Numpy (Part I)
  • Deep Dive Into Numpy (Part II)

1 Readings

  • Numpy, Pandas, and scikit-learn

Introduction to Pandas

    • 2 Videos
    • 1 Readings
    • 1 Lab
    • 1 Assignment
Show info about module content

1 Assignment

  • Practice Quiz: Pandas

1 Labs

  • Indexing DataFrames

2 Videos

  • Introduction to Pandas
  • Pandas Deep Dive

1 Readings

  • 10 min to Pandas

Combining and Reshaping Data

    • 3 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Combining Data

3 Videos

  • Joining and Manipulating Dataframes (I)
  • Joining and Manipulating Dataframes (II)
  • Joining and Manipulating Dataframes (III)

1 Readings

  • Pandas Docs: Reshaping and Combining Data

Grouping and Sorting

    • 2 Readings
    • 1 Assignment
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1 Assignment

  • Numpy and Pandas Quiz

2 Readings

  • Split-Apply-Combine
  • Python Docs: Sort_values()

Finding Outliers

    • 1 Lab
    • 1 Programming
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1 Programming

  • Finding Outliers

1 Labs

  • Programming Assignment Solutions: Finding Outliers

Introduction to Scikit-Learn

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Using the scikit-learn Docs

2 Videos

  • Module Introduction
  • Using the Scikit-Learn Docs

1 Readings

  • Introduction to scikit-learn

Loading and Analyzing Datasets

    • 1 Videos
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Loading and Analyzing Data

1 Labs

  • Programming Assignment Solutions: Loading and Analyzing Data

1 Videos

  • Loading and Analyzing datasets

Machine Learning in Scikit-Learn (Regression)

    • 1 Videos
    • 1 Readings
    • 1 Discussion
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1 Discussions

  • Neural Networks: A Black Box?

1 Videos

  • Applying Linear Regression (I)

1 Readings

  • Train/Test Split and Cross-Validation

Machine learning in Scikit-Learn Continued

    • 2 Videos
    • 1 Readings
    • 1 Assignment
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1 Assignment

  • Practice Quiz: Math of Linear Regression

2 Videos

  • Math of Machine Learning
  • Scikit-Learn Conclusion

1 Readings

  • Least Squares

Final Quiz

    • 1 Assignment
Show info about module content

1 Assignment

  • Linear Regression with Scikit-Learn

Classification: Predicting Heart Disease

    • 1 Videos
    • 1 Lab
    • 1 Programming
Show info about module content

1 Programming

  • Predicting the Presence of Heart Disease

1 Labs

  • Programming Assignment Solutions: Predicting the Presence of Heart Disease

1 Videos

  • Predicting the Presence of Heart Disease

Auto Summary

Unlock the power of Python and artificial intelligence with the comprehensive "Introduction to Data Science and scikit-learn in Python" course, designed specifically for those eager to dive into the world of data science and AI. Guided by expert instructors from Coursera, this foundational course spans 840 minutes of engaging content, taking you from the basics of Python to the intricacies of data analysis and machine learning. You'll begin with essential Python programming skills tailored for data science applications. Progressing through the course, you'll explore key libraries such as Numpy, Pandas, and scikit-learn, crucial for conducting exploratory data analysis (EDA) and building machine learning models. A unique feature of this course is its practical approach: you'll learn the theory and mathematics behind linear regression, followed by hands-on experience in reading, cleaning, and modeling data. Specifically, you'll estimate the progression of diabetes using a regression model and predict the presence or absence of heart disease with a classification model based on patient health data. Whether you're a beginner or looking to strengthen your foundation in data science, this course offers valuable insights and practical skills. Enroll with a Starter subscription to begin your journey into data science and artificial intelligence today!

Sabrina Moore
Instructors

Sabrina Moore

Rajvir Dua
Instructors

Rajvir Dua

Neelesh Tiruviluamala
Instructors

Neelesh Tiruviluamala