Applied Data Science


This action-packed Specialization by IBM equips data science enthusiasts with practical skills for real-world data problems. The 4-course program focuses on Python, data analysis, and data visualization, offering hands-on experience in tackling interesting data problems from start to finish.

Participants will gain proficiency in Python fundamentals, practical Python skills for data analysis, effective communication of data insights through visualizations, and the creation of a project demonstrating applied data science techniques and tools.

Upon completion, learners will earn a Specialization completion certificate from Coursera and a digital badge from IBM, with the option to apply this program toward the IBM Data Science Professional Certificate. Additionally, completing the program can earn up to 12 college credits (ACEĀ® recommended).

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Applied Data Science
Course Modules

The 4-course Specialization covers Python fundamentals, practical Python skills for data analysis, data visualization techniques, and a capstone project applying data science and machine learning techniques to a real-world dataset.

Python for Data Science, AI & Development

Module 1: Python for Data Science, AI & Development

  • Describe Python basics and data structures
  • Apply Python programming logic and libraries like Pandas and Numpy
  • Access web data using APIs and web scraping from Python in Jupyter Notebooks

Python Project for Data Science

Module 2: Python Project for Data Science

  • Demonstrate skills in Python for data science and analysis
  • Build a dashboard using Python and libraries like Pandas, Beautiful Soup, and Plotly

Data Analysis with Python

Module 3: Data Analysis with Python

  • Develop Python code for cleaning and preparing data for analysis
  • Perform exploratory data analysis and apply analytical techniques using libraries like Pandas and Numpy
  • Build and evaluate regression models using machine learning scikit-learn library

Data Visualization with Python

Module 4: Data Visualization with Python

  • Implement data visualization techniques and plots using Python libraries like Matplotlib, Seaborn, and Folium
  • Create different types of charts and advanced visualizations
  • Generate interactive dashboards using the Dash framework and Plotly library

Applied Data Science Capstone

Module 5: Applied Data Science Capstone

  • Demonstrate proficiency in data science and machine learning techniques using a real-world data set
  • Apply skills to perform data collection, data wrangling, exploratory data analysis, data visualization, and model development
  • Write Python code to create machine learning models and evaluate their results for predictive analysis
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