Python for Data Science Course
Bring Strategy to AI-Powered Analysis
Gain the technical expertise to design, write, and deploy production-ready Python code. Transform complex data into actionable insights with this rigorous, highly technical 9-week online course from UChicago.
| Course | Format | Duration | Investment | CEU's | Next Course |
|---|---|---|---|---|---|
Python for Data Science |
Online (live sessions) | 9 weeks | $2,800 | 5.2 Continuing Education Units | Next Start: Autumn 2026 |
Designed for Quantitative Minds
This course provides a comprehensive practical foundation in Python for data science, equipping you with the coding discipline, analytical techniques, and model-building capabilities essential for current tech-related roles. This program is built for:
- Data Analysts working predominantly in Excel, looking to upgrade to a technical toolkit.
- Business Intelligence Analysts with strong theory but limited Python exposure.
- Technical Professionals looking to transition into data science or machine learning engineering.
- Quantitative Professionals eager for a structured, academic approach to coding discipline.
Be In-Demand
Python is one of the most popular and versatile programming languages. It is widely used in data science, machine learning, and web development.
By the end of the course, you will be able to:
- Write efficient, scalable, and production-ready Python code.
- Perform advanced data manipulation on high volumes of data.
- Design and optimize code for maximum performance and speed.
- Prepare and monitor machine learning models in production environments.
Available positions requiring familiarity with Python are on the rise; world-class companies like Accenture, Amazon, Apple, Deloitte, Google, Microsoft, and Netflix are among those behind the significant jump in job openings for Python developers.
Methodologies and Techniques
Anaconda
Beautiful Soup
Jupyter
NumPy
pandas
Python
scikit learn
seaborn
An Nine-Week Deep Dive into Data Engineering & Machine Learning
What You'll Learn
- Week 1: Getting Started with Python – An onboarding and technical setup module. It provides the foundational tools, environment configuration, and platform familiarity necessary to succeed in the course.
- Week 2: Foundational Python Functionality – Iteration, error handling, and the collections module.
- Week 3: User-Defined Functions and Classes – Creating UDFs, lambda functions, and linear regression classes.
- Week 4: Basic Data Analysis and Manipulation – Mastery of pandas and NumPy for summary statistics.
- Week 5: Advanced Data Analysis and Manipulation – Broadcasting, matrix operations, and rolling metrics.
- Week 6: Training and Evaluating Machine Learning Models – Feature extraction and model training with Scikit-learn.
- Week 7: Parallelizing Model Training and Programs Using Multiprocessing – Using generators and the multiprocessing module for efficiency.
- Week 8: Parallelizing Web Scrapers Using Multithreading – Parallel web scraping with Beautiful Soup and ThreadPoolExecutor.
- Week 9: Model Deployment – Saving models, batch predictions, and API deployment.
FAQ
No, it features live, interactive sessions for maximum engagement.
A rudimentary knowledge of Python and machine learning is recommended.
