VOOZH about

URL: https://www.coursera.org/learn/python-fundamentals

⇱ Python Fundamentals | Coursera


Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.

Gain insight into a topic and learn the fundamentals.
4.9

13 reviews

Advanced level
Designed for those already in the industry
6 hours to complete
Flexible schedule
Learn at your own pace

Gain insight into a topic and learn the fundamentals.
4.9

13 reviews

Advanced level
Designed for those already in the industry
6 hours to complete
Flexible schedule
Learn at your own pace

Build your subject-matter expertise

This course is part of the Practical Data Science for Data Analysts Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • 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

There are 8 modules in this course

Python is the most popular programming language used for data science and is a must-know to start or advance your career in data.

In this course, you will learn the most fundamental skills to write and execute Python code. We will have an overview of the basic Python concepts, which will enable you to get started with a data science project! You will see how to load, clean, analyze, and transform data with two popular Python packages: Numpy and Pandas. Then, we will demonstrate how to effectively communicate the key insights from your analysis by visualizing your data using the Matplotlib and Seaborn packages. Finally, you’ll combine these skills and put your new knowledge into practice by analyzing financial data through a case study. Upon completing this course, you will be able to: β€’ Write and execute Python code to create variables, generate outputs, apply various operators, and manipulate different types of data β€’ Capture and transform data using Numpy and Pandas packages β€’ Explore data through different statistical methods to gain a deeper understanding β€’ Visualize data to share insights using the Matplotlib and Seaborn packages β€’ Combine and apply the skills above to analyze financial data This Python Fundamentals course is perfect for anyone who would like to build up their programming skills and use Python for data science to analyze data. This course is designed to equip anyone who desires to begin or further their career in data analysis, quantitative analysis, business intelligence, or other areas of business and finance.

In this course, we will learn the most fundamental skills to write and execute Python code. We will have an overview of the basic Python concepts, which will enable you to get started with a data science project! We will see how to load, clean, analyze, and transform data with two popular Python packages: Numpy and Pandas. Then, we will demonstrate how to effectively communicate the key insights from your analysis by visualizing your data using the Matplotlib and Seaborn packages. Finally, you’ll combine these skills and put your new knowledge into practice by analyzing financial data through a case study.

What's included

5 videos1 reading

5 videosβ€’Total 9 minutes
  • Course Introductionβ€’2 minutes
  • Instructions to download Learner Filesβ€’1 minute
  • Install Anacondaβ€’1 minute
  • Python Development Environmentsβ€’2 minutes
  • Jupyter Notebook Overviewβ€’4 minutes
1 readingβ€’Total 10 minutes
  • Downloadable Learner Filesβ€’10 minutes

What's included

24 videos4 plugins

24 videosβ€’Total 62 minutes
  • Introduction - Python Conceptsβ€’1 minute
  • Variables & Data Typesβ€’1 minute
  • Assigning Variablesβ€’3 minutes
  • Printing Variablesβ€’2 minutes
  • Reassigning Variablesβ€’2 minutes
  • Basic Data Typesβ€’4 minutes
  • Working with Stringsβ€’3 minutes
  • Convert & Combine Data Typesβ€’3 minutes
  • Data Structuresβ€’1 minute
  • Listsβ€’5 minutes
  • Manipulating Listsβ€’4 minutes
  • Tuplesβ€’3 minutes
  • Dictionariesβ€’4 minutes
  • Operators & Functionsβ€’1 minute
  • Mathematical Operatorsβ€’3 minutes
  • Comparison Operatorsβ€’2 minutes
  • Logical Operatorsβ€’3 minutes
  • Built-in Functionsβ€’2 minutes
  • Packagesβ€’4 minutes
  • Conditional Statements & For Loopsβ€’1 minute
  • If Statementβ€’2 minutes
  • Else & Elif Statementsβ€’3 minutes
  • For Loopsβ€’5 minutes
  • Summary - Python Conceptsβ€’1 minute
4 pluginsβ€’Total 31 minutes
  • Interactive Exercise 1β€’10 minutes
  • Interactive Exercise 2β€’10 minutes
  • Interactive Exercise 3β€’1 minute
  • Interactive Exercise 4β€’10 minutes

What's included

19 videos

19 videosβ€’Total 38 minutes
  • Introduction - Loading & Cleaning Dataβ€’1 minute
  • Introduction to NumPy & Pandasβ€’1 minute
  • NumPy Arraysβ€’3 minutes
  • Operations with NumPy Arraysβ€’2 minutes
  • Pandas Seriesβ€’4 minutes
  • Operations with Pandas Seriesβ€’3 minutes
  • Pandas DataFrameβ€’2 minutes
  • Loading Dataβ€’1 minute
  • Generating Data with NumPy arange()β€’3 minutes
  • Generating Data with NumPy random()β€’3 minutes
  • Importing External Data with Packagesβ€’2 minutes
  • Importing External .CSVβ€’1 minute
  • Cleaning Dataβ€’1 minute
  • Changing Data Typesβ€’2 minutes
  • Cleaning Missing Dataβ€’3 minutes
  • Cleaning Duplicate Dataβ€’2 minutes
  • Cleaning Incorrect Data & Exportingβ€’2 minutes
  • Loading & Cleaning Data Exerciseβ€’1 minute
  • Loading & Cleaning Data Exercise Reviewβ€’3 minutes

What's included

16 videos

16 videosβ€’Total 37 minutes
  • Introduction - Analyzing Dataβ€’1 minute
  • Transforming Dataβ€’1 minute
  • Selecting Data from a DataFrameβ€’3 minutes
  • Selecting Data with loc() & iloc()β€’4 minutes
  • Selecting Data with a Conditional Statementβ€’3 minutes
  • Adding & Removing Data from a DataFrameβ€’5 minutes
  • Creating a New Indexβ€’1 minute
  • Grouping Dataβ€’2 minutes
  • Concatenating DataFramesβ€’2 minutes
  • Statistical Analysisβ€’1 minute
  • Describing Single Variable Statisticsβ€’3 minutes
  • Calculating a Z-scoreβ€’2 minutes
  • Identifying Outliersβ€’3 minutes
  • Measuring Correlationβ€’3 minutes
  • Analyzing Data Exerciseβ€’1 minute
  • Analyzing Data Exercise Reviewβ€’4 minutes

What's included

18 videos

18 videosβ€’Total 52 minutes
  • Introduction - Visualizing Dataβ€’1 minute
  • Visualizing Data for Exploratory Analysisβ€’1 minute
  • Building the DataFrames to Visualizeβ€’3 minutes
  • Updating the DataFrames to Visualizeβ€’3 minutes
  • Creating Histogramsβ€’4 minutes
  • Creating Box Plotsβ€’3 minutes
  • Creating a Pairplotβ€’2 minutes
  • Creating a Correlation Matrix Heatmapβ€’5 minutes
  • Visualizing Data for Sharing Insightsβ€’1 minute
  • Rebuilding the DataFrames to Visualizeβ€’2 minutes
  • Creating Line Chartsβ€’2 minutes
  • Formatting Line Chartsβ€’5 minutes
  • Creating Bar Plotsβ€’2 minutes
  • Formatting Bar Plotsβ€’4 minutes
  • Creating Scatter Plotsβ€’3 minutes
  • Formatting Scatter Plotsβ€’5 minutes
  • Visualizing Data Exerciseβ€’1 minute
  • Visualizing Data Exercise Reviewβ€’6 minutes

What's included

12 videos

12 videosβ€’Total 40 minutes
  • Case Study Introduction - Portfolio Optimizationβ€’2 minutes
  • Import Packages & Connect to Dataβ€’4 minutes
  • Create the Equal-Weighted Portfolioβ€’4 minutes
  • Visualize the Portfolio Performanceβ€’4 minutes
  • Calculate Performance Metrics for the Portfolioβ€’4 minutes
  • Calculate the Sharpe Ratio for the Portfolioβ€’2 minutes
  • Prepare Scenarios to Optimize Portfolio Weightingβ€’3 minutes
  • Build the Portfolio Scenariosβ€’6 minutes
  • Generate the Portfolio Scenariosβ€’3 minutes
  • Identify the Optimal Portfolioβ€’2 minutes
  • Visualize the Optimal Portfolio & Portfolio Scenariosβ€’4 minutes
  • Case Study Summary - Portfolio Optimizationβ€’2 minutes

What's included

1 video

1 videoβ€’Total 1 minute
  • Course Summaryβ€’1 minute

What's included

1 assignment

1 assignmentβ€’Total 75 minutes
  • Qualified Assessmentβ€’75 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructor

Corporate Finance Institute
47 Coursesβ€’146,269 learners

Explore more from Finance

Why people choose Coursera for their career

πŸ‘ Image

Felipe M.

Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
πŸ‘ Image

Jennifer J.

Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
πŸ‘ Image

Larry W.

Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
πŸ‘ Image

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

  • 5 stars

    92.30%

  • 4 stars

    7.69%

  • 3 stars

    0%

  • 2 stars

    0%

  • 1 star

    0%

Showing 3 of 13

SB
Β·

Reviewed on Nov 9, 2025

Really interesting course, well done and clear.

Very good to learn fundamentals

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. 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 Specialization, 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.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,