Python for Data Science, AI & Development

Python for Data Science, AI & Development

This course is part of multiple programs.

Instructor: Joseph Santarcangelo

What you'll learn

Learn Python - the most popular programming language and for Data Science and Software Development.
Apply Python programming logic Variables, Data Structures, Branching, Loops, Functions, Objects & Classes.
Demonstrate proficiency in using Python libraries such as Pandas & Numpy, and developing code using Jupyter Notebooks.
Access and web scrape data using APIs and Python libraries like Beautiful Soup.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

22 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

Build your subject-matter expertise

This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 5 modules in this course

Kickstart your learning of Python with this beginner-friendly self-paced course taught by an expert. Python is one of the most popular languages in the programming and data science world and demand for individuals who have the ability to apply Python has never been higher.

This introduction to Python course will take you from zero to programming in Python in a matter of hours—no prior programming experience necessary! You will learn about Python basics and the different data types. You will familiarize yourself with Python Data structures like List and Tuples, as well as logic concepts like conditions and branching. You will use Python libraries such as Pandas, Numpy & Beautiful Soup. You’ll also use Python to perform tasks such as data collection and web scraping with APIs. You will practice and apply what you learn through hands-on labs using Jupyter Notebooks. By the end of this course, you’ll feel comfortable creating basic programs, working with data, and automating real-world tasks using Python. This course is suitable for anyone who wants to learn Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps as well as a number of other job roles.

This module teaches the basics of Python and begins by exploring some of the different data types such as integers, real numbers, and strings. Continue with the module and learn how to use expressions in mathematical operations, store values in variables, and the many different ways to manipulate strings.

What's included

6 videos5 readings4 assignments4 app items3 plugins

6 videosTotal 20 minutes

Course Introduction1 minutePreview module
Introduction to Python4 minutes
Getting Started with Jupyter4 minutes
Types3 minutes
Expressions and Variables3 minutes
String Operations4 minutes

5 readingsTotal 21 minutes

About this course2 minutes
Course Overview2 minutes
Helpful Tips for Course Completion2 minutes
Introduction to Jupyter10 minutes
Module 1 Summary: Python Basics 5 minutes

4 assignmentsTotal 48 minutes

Module 1 Graded Quiz: Python Basics 30 minutes
Practice Quiz: Types6 minutes
Practice Quiz: Expressions and Variables6 minutes
Practice Quiz: String Operations6 minutes

4 app itemsTotal 60 minutes

Hands-on Lab: Write Your First Program10 minutes
Hands-on Lab: Types10 minutes
Hands-on Lab: Expression and Variables10 minutes
Hands-On Lab: String Operations30 minutes

3 pluginsTotal 26 minutes

(Optional) Reading: Format Strings in Python5 minutes
Cheat Sheet: Python Basics 15 minutes
Module 1 Glossary: Python Basics 6 minutes

This module begins a journey into Python data structures by explaining the use of lists and tuples and how they are able to store collections of data in a single variable. Next learn about dictionaries and how they function by storing data in pairs of keys and values, and end with Python sets to learn how this type of collection can appear in any order and will only contain unique elements.

What's included

3 videos1 reading4 assignments4 app items3 plugins

3 videosTotal 16 minutes

Lists and Tuples8 minutesPreview module
Dictionaries2 minutes
Sets5 minutes

1 readingTotal 5 minutes

Module 2 Summary: Python Data Structures 5 minutes

4 assignmentsTotal 52 minutes

Module 2 Graded Quiz: Python Data Structures30 minutes
Practice Quiz: Lists and Tuples10 minutes
Practice Quiz: Dictionaries6 minutes
Practice Quiz: Sets6 minutes

4 app itemsTotal 95 minutes

Hands-On Lab: Lists30 minutes
Hands-On Lab: Tuples15 minutes
Hands-On Lab: Dictionaries30 minutes
Hands-On Lab: Sets20 minutes

3 pluginsTotal 34 minutes

Cheat Sheet: Lists and Tuples15 minutes
CheatSheet: Dictionaries & Sets15 minutes
Module 2 Glossary: Python Data Structures4 minutes

This module discusses Python fundamentals and begins with the concepts of conditions and branching. Continue through the module and learn how to implement loops to iterate over sequences, create functions to perform a specific task, perform exception handling to catch errors, and how classes are needed to create objects.

What's included

5 videos1 reading6 assignments6 app items7 plugins

5 videosTotal 45 minutes

Conditions and Branching10 minutesPreview module
Loops6 minutes
Functions13 minutes
Exception Handling3 minutes
Objects and Classes10 minutes

1 readingTotal 5 minutes

Module 3 Summary: Python Programming Fundamentals5 minutes

6 assignmentsTotal 68 minutes

Module 3 Graded Quiz: Python Programming Fundamentals 30 minutes
Practice Quiz: Conditions and Branching8 minutes
Practice Quiz: Loops6 minutes
Practice Quiz: Functions8 minutes
Practice Quiz: Exception Handling6 minutes
Practice Quiz: Objects and Classes10 minutes

6 app itemsTotal 180 minutes

Hands-On Lab: Conditions and Branching20 minutes
Hands-On Lab: Loops20 minutes
Hands-On Lab: Functions40 minutes
Hands-On Lab: Exception Handling15 minutes
Hands-On Lab: Objects and Classes40 minutes
Practice Lab: Text Analysis45 minutes

7 pluginsTotal 85 minutes

Reading: Conditions and Branching10 minutes
Reading: Introduction to Loops in Python10 minutes
Reading: Exploring Python Functions15 minutes
Reading: Exception Handling10 minutes
Reading: Objects and Classes10 minutes
Cheat Sheet: Python Programming Fundamentals15 minutes
Module 3 Glossary: Python Programming Fundamentals15 minutes

This module explains the basics of working with data in Python and begins the path with learning how to read and write files. Continue the module and uncover the best Python libraries that will aid in data manipulation and mathematical operations.

What's included

6 videos1 reading4 assignments6 app items8 plugins

6 videosTotal 32 minutes

Reading Files with Open3 minutesPreview module
Writing Files with Open2 minutes
Pandas: Loading Data4 minutes
Pandas: Working with and Saving Data2 minutes
One Dimensional Numpy11 minutes
Two Dimensional Numpy7 minutes

1 readingTotal 5 minutes

Module 4 Summary: Working with Data in Python 5 minutes

4 assignmentsTotal 54 minutes

Module 4 Graded Quiz: Working with Data in Python30 minutes
Practice Quiz: Reading and Writing Files with Open8 minutes
Practice Quiz: Pandas10 minutes
Practice Quiz: Numpy in Python6 minutes

6 app itemsTotal 190 minutes

Hands-On Lab: Reading Files with Open30 minutes
Hands-On Lab: Writing Files with Open30 minutes
Practice Lab: Selecting Data in a DataFrame30 minutes
Hands on Lab: Loading Data with Pandas30 minutes
Hands-On Lab: One Dimensional Numpy40 minutes
Hands-On Lab: Two Dimensional Numpy30 minutes

8 pluginsTotal 76 minutes

Reading: Reading Files with Open10 minutes
Reading: Writing Files with Open10 minutes
Reading: Pandas15 minutes
Reading: Matrix Mathematics5 minutes
Reading: Beginner's Guide to NumPy10 minutes
Reading: Some Context on APIs5 minutes
Cheat Sheet: Working with Data in Python15 minutes
Module 4 Glossary: Working with Data in Python 6 minutes

This module delves into the unique ways to collect data by the use of APIs and web scraping. It further explores data collection by explaining how to read and collect data when dealing with different file formats.