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Predictive Data Analysis with Python
Learn predictive data analysis with Python using NumPy, Pandas, Matplotlib, and Seaborn. Apply skills to real-world finance and advertising projects to extract and visualize insights.
62 Lessons
10h
Updated today
Join 2.9 million developers at
Join 2.9 million developers at
LEARNING OBJECTIVES
- Define data analysis concepts and the role of Python libraries like NumPy, Pandas, Matplotlib, and Seaborn in predictive data analysis.
- Create and manipulate 1-D and 2-D NumPy arrays using essential functions for effective data handling.
- Utilize Pandas DataFrames for data cleaning, manipulation, and preparation for predictive analysis.
- Apply statistical features and probability distributions to analyze and interpret quantitative data.
- Implement data visualization techniques using Matplotlib and Seaborn to represent data insights effectively.
- Conduct predictive modeling and analysis using real-world datasets in finance and advertising.
KEY OUTCOMES
Ace Predictive Data Analysis
Demonstrate the ability to analyze and predict outcomes using Python, showcasing skills in data manipulation and statistical reasoning.
Build Robust Data Models
Create and implement predictive models using NumPy and Pandas, enabling accurate forecasting in real-world scenarios.
Visualize Complex Data Insights
Effectively communicate data findings through visualizations, using Matplotlib and Seaborn to enhance data storytelling.
Optimize Marketing Strategies
Leverage customer behavior analysis to inform marketing decisions, applying RFM analysis for targeted campaigns.
Learning Roadmap
2.
Numpy for Python
Numpy for Python
Get started with creating, indexing, transposing, and processing NumPy arrays for efficient data analysis.
3.
Pandas for Python
Pandas for Python
12 Lessons
12 Lessons
Go hands-on with data manipulation using Pandas in Python for predictive analysis.
4.
Statistics for Data Analysis
Statistics for Data Analysis
3 Lessons
3 Lessons
Grasp the fundamentals of statistical features, probability distributions, and the Central Limit Theorem.
5.
Data Wrangling
Data Wrangling
12 Lessons
12 Lessons
Take a closer look at managing, reshaping, and cleaning data for effective analysis.
6.
Visualizing the Data
Visualizing the Data
9 Lessons
9 Lessons
Follow the process of using visualization tools to analyze and represent data.
7.
Data Scraping
Data Scraping
4 Lessons
4 Lessons
Master the steps to scrape web data using Python and Selenium for analysis.
8.
Project #1
Project #1
6 Lessons
6 Lessons
Try out stock market analysis, price trends, daily returns, correlations, risk, and predictions.
9.
Project #2
Project #2
5 Lessons
5 Lessons
Unpack the core of customer behavior, brand preference, user activity, and RFM segmentation.
10.
Conclusion
Conclusion
2 Lessons
2 Lessons
Examine essential tools, techniques, and next steps for predictive data analysis with Python.
Certificate of Completion
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Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
Predictive data analysis with Python has become a foundational skill in today’s data-driven economy, where organizations rely on accurate forecasting to guide everything from product strategy to revenue optimization. As machine learning systems become more embedded in decision-making, the ability to not just analyze data but predict outcomes is what separates entry-level analysts from high-impact practitioners.
I built this course from my work in intelligent computing and adaptive AI systems, where predictive modeling is central to designing responsive, data-aware applications. During my research and applied work in neural networks and intelligent tutoring systems, I repeatedly saw a gap: learners could manipulate data, but struggled to translate it into forward-looking insights. This course is designed to close that gap with a structured, practical approach.
You’ll learn predictive data analysis with Python through a progression of statistical reasoning, feature engineering, and model building using NumPy, Pandas, Matplotlib, and Seaborn. Each concept is grounded in real-world datasets and culminates in applied projects across finance and advertising domains.
Thousands of learners have used this approach to transition into data-focused roles. If you want to move beyond analysis into prediction, this is where you begin.
ABOUT THE AUTHOR
Khayyam Hashmi
Computer scientist and Generative AI and Machine Learning specialist. VP of Technical Content @ educative.io.
Trusted by 2.9 million developers working at companies
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Anthony Walker
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Evan Dunbar
ML Engineer
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Software Developer
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Front-end Developer
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Vinay Krishnaiah
Software Developer
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