Python for Data Science, AI & Development

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Python for Data Science, AI & Development

This course is part of multiple programs.

Instructor: Joseph Santarcangelo

1,219,430 already enrolled

Included with Coursera Plus

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5 modules

Gain insight into a topic and learn the fundamentals.

4.6

(41,368 reviews)

Beginner level

Recommended experience

Flexible schedule

7 hours to complete

Learn at your own pace

95%

Most learners liked this course

5 modules

Gain insight into a topic and learn the fundamentals.

4.6

(41,368 reviews)

Beginner level

Recommended experience

Flexible schedule

7 hours to complete

Learn at your own pace

95%

Most learners liked this course

What you'll learn

Develop a foundational understanding of Python programming by learning basic syntax, data types, expressions, variables, and string operations.
Apply Python programming logic using data structures, conditions and branching, loops, functions, exception handling, objects, and classes.
Demonstrate proficiency in using Python libraries such as Pandas and Numpy and developing code using Jupyter Notebooks.
Access and extract web-based data by working with REST APIs using requests and performing web scraping with BeautifulSoup.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

22 assignments

Taught in English

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Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

Kickstart your Python journey with this beginner-friendly, self-paced course taught by an expert. Python is one of the most popular programming languages, and the demand for individuals with Python skills continues to grow.

This course takes you from zero to programming in Python in a matter of hours—no prior programming experience is necessary! You’ll begin with Python basics, including data types, expressions, variables, and string operations. You will explore essential data structures such as lists, tuples, dictionaries, and sets, learning how to create, access, and manipulate them. Next, you will delve into logic concepts like conditions and branching, learning how to use loops and functions, along with important programming principles like exception handling and object-oriented programming. As you progress, you will gain practical experience reading from and writing to files and working with common file formats. You’ll also use powerful Python libraries like NumPy and Pandas for data manipulation and analysis. The course also covers APIs and web scraping, teaching you how to interact with REST APIs using libraries like requests and extract data from websites using BeautifulSoup. 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 individuals interested in pursuing careers in Data Science, Data Analytics, Software Development, Data Engineering, AI, and DevOps and a variety of other technology-related 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 Operations3 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 items7 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

7 pluginsTotal 71 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
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.

What's included

6 videos3 readings4 assignments6 app items6 plugins

6 videosTotal 28 minutes

Application Program Interface5 minutesPreview module
REST APIs & HTTP Requests - Part 14 minutes
REST APIs & HTTP Requests - Part 24 minutes
(Optional) HTML for Web Scraping4 minutes
(Optional) Web Scraping 4 minutes
Working with Different File Formats 4 minutes

3 readingsTotal 17 minutes

Module 5 Summary: APIs and Data Collection5 minutes
Congratulations and Next Steps2 minutes
Python Cheat Sheet: The Basics10 minutes

4 assignmentsTotal 108 minutes

Module 5 Graded Quiz: APIs and Data Collection15 minutes
Final Exam for the Course75 minutes
Practice Quiz: Simple APIs 6 minutes
Practice Quiz: REST APIs, Web Scraping, and Working with Files12 minutes

6 app itemsTotal 185 minutes

Hands-On Lab: Introduction to API15 minutes
Hands-on Lab: Access REST APIs & Request HTTP30 minutes
Hands-On Lab: API Examples30 minutes
Hands-on Lab: Web Scraping40 minutes
Practice Project: GDP Data Extraction and Processing30 minutes
Hands-on Lab: Working with different file formats40 minutes

6 pluginsTotal 51 minutes

Reading: Some Context on APIs5 minutes
Reading: Web Scraping and HTML Basics10 minutes
Reading: Web Scraping - A Key Tool in Data Science5 minutes
Reading: Web Scraping Tables using Pandas5 minutes
Cheat Sheet: APIs and Data Collection15 minutes
Module 5 Glossary: APIs and Data Collection11 minutes

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Instructor

Instructor ratings

4.5 (8,992 ratings)

Joseph Santarcangelo

IBM

35 Courses1,973,566 learners

Offered by

IBM

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Learner reviews

4.6

41,368 reviews

5 stars
72.09%
4 stars
20.68%
3 stars
4.38%
2 stars
1.43%
1 star
1.38%

Showing 3 of 41368

Reviewed on Oct 19, 2022

This was an extremely informative course and I believe is perfect way to strt off your coding journey. The teaching style was understandable.detail oriented and very practical. Highly Recommended.

Reviewed on Dec 11, 2019

All the basics for Data Science with Python. You wont be a master programmer after this class but you will understand the basics and computer logic in regards to data handling and cloud management.

Reviewed on May 30, 2019

The cloud storage question on the final is just a ploy to get us to use IBM products and shouldn't be part of the grade. The course was a good pace and nice, slow introduction for new Python users.

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Frequently asked questions

To earn an IBM Badge that recognizes your competence in Python for data science and AI, take this course as part of one of the following programs:

- IBM Applied AI Professional Certificate

- Applied Data Science Specialization

- IBM Data Science Professional Certificate

This course consists of four modules.

Module 1 - Python Basics

oYour first program

oTypes

oExpressions and Variables

oString Operations

Module 2 - Python Data Structures

oLists and Tuples

oSets

oDictionaries

Module 3 - Python Programming Fundamentals

oConditions and Branching

oLoops

oFunctions

oObjects and Classes

Module 4 - Working with Data in Python

oReading files with open

oWriting files with open

oLoading data with Pandas

oNumpy

Finally, you will create a project to test your skills.

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.