IBM Data Science Professional Certificate Program Guide
Validates practical skills in Python, SQL, data analysis, visualization, machine learning and generative AI tools for data science.
Work through 12 courses in order, from data science basics and tools to Python, SQL, data analysis, visualization and machine learning, then a capstone, generative AI and career preparation. Complete the labs and graded assessments. There is no final exam.
1Understand the program
Courses
Rows are courses with Coursera's hour estimates.
Course 1What is Data Science? (12 hours)
Module 1Defining Data Science and What Data Scientists Do
Module 2Data Science Topics
Module 3Applications and Careers in Data Science
Module 4Data literacy for Data Science (Optional)
Course 2Tools for Data Science (16 hours)
Module 1Overview of Data Science Tools
Module 2Languages of Data Science
Module 3Packages, APIs, Data Sets, and Models
Module 4Jupyter Notebooks and JupyterLab
Module 5RStudio & GitHub
Module 6Final Project and Submission
Course 3Data Science Methodology (9 hours)
Module 1From Problem to Approach and From Requirements to Collection
Module 2From Understanding to Preparation and From Modeling to Evaluation
Module 3From Deployment to Feedback and Final Evaluation
Module 4Final Project and Assessment
Example scenario: A bike-share company wants to reduce empty stations. Which question would you ask first, and what data would you need to answer it?
Course 4Python for Data Science, AI & Development (24 hours)
Module 1Python Basics
Module 2Python Data Structures
Module 3Python Programming Fundamentals
Module 4Working with Data in Python
Module 5APIs and Data Collection
Course 5Python Project for Data Science (7 hours)
Module 1Crowdsourcing Short squeeze Dashboard
Module 2Final Project
Course 6Databases and SQL for Data Science with Python (18 hours)
Module 1Getting Started with SQL
Module 2Introduction to Relational Databases and Tables
Module 3Intermediate SQL
Module 4Accessing Databases using Python
Module 5Course Assignment
Module 6Bonus Module: Advanced SQL for Data Engineers
Example scenario: You have one table of customers and one of orders. How would you list customers who have not ordered in the last 90 days?
Course 7Data Analysis with Python (16 hours)
Module 1Importing Data Sets
Module 2Data Wrangling
Module 3Exploratory Data Analysis
Module 4Model Development
Module 5Model Evaluation and Refinement
Module 6Final Assignment
Course 8Data Visualization with Python (19 hours)
Module 1Introduction to Data Visualization Tools
Module 2Basic and Specialized Visualization Tools
Module 3Advanced Visualizations and Geospatial Data
Module 4Creating Dashboards with Plotly and Dash
Module 5Final Project and Exam
Course 9Machine Learning with Python (20 hours)
Module 1Introduction to Machine Learning
Module 2Linear and Logistic Regression
Module 3Building Supervised Learning Models
Module 4Building Unsupervised Learning Models
Module 5Evaluating and Validating Machine Learning Models
Module 6Final Project and Exam
Example scenario: A model predicts loan defaults with 95% accuracy, but only 5% of customers default. Why might accuracy be misleading here?
Course 10Applied Data Science Capstone (14 hours)
Module 1Introduction
Module 2Exploratory Data Analysis (EDA)
Module 3Interactive Visual Analytics and Dashboard
Module 4Predictive Analysis (Classification)
Module 5Present Your Data-Driven Insights
Course 11Generative AI: Elevate Your Data Science Career (14 hours)
Module 1Data Science and Generative AI
Module 2Use of Generative AI for Data Science
Module 3Final Project and Exam
Course 12Data Scientist Career Guide and Interview Preparation (9 hours)
Coursera's course estimates add up to 178 hours, and Coursera suggests 4 months at 10 hours a week.
Most candidates spend 100–200 hours. Coursera's course estimates add up to 178 hours. Plan for the low end if you already code in Python; plan for the high end if Python and machine learning are new to you.
1Understand the programLook through the courses and how the program is graded.9 h
3Learn the core conceptsWork through the courses in order and complete the graded work.160 h
4Finish the programFinish the remaining assessments and claim your certificate.9 h
3Learn the core concepts
The program is the course. Build a second project of your own alongside the capstone.
Hiring managers in r/datascience said they look at project work and applied answers rather than certificates. In a 2025 thread, one hirer said a capstone published to a repo or served as a Streamlit, Flask or Gradio app would impress them.
Best official programIBM Data Science Professional Certificate