Your Introduction to Data Science, Tuition-Free
Advance your current job with skills in high demand
Starting with a full introduction to Python and covering the most essential data science tools, students will learn how to turn business metrics into valuable insights.
Start a career in data science and analytics
All students are given complimentary access to a pre-configured development environment for the entire module, helping them learn Python, pandas, and Jupyter Notebooks hands-on.
Prepare for a future in Financial Engineering
Graduates will receive a certificate of completion. The Introduction to Data Science module is built by The Data Incubator, a fellowship program that trains data scientists.
The process is fast, easy, and straightforward.
ApplyThe Module
The Introduction To Data Science module is delivered online so that students can earn their certificate without disrupting their life.
In just two months, students will be able to source data relevant to a business problem or task, summarize data in aggregate statistics and visualizations, and model trends to show insights and make practical business decisions.
- Programming fundamentals, basic Python, and control flow
- Python data types and data structures
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Classes and object-oriented programming
Basic data analysis in Python: NumPy, Matplotlib, and pandas -
Data file formats and data parsing
Data aggregation and visualization with pandas - Basic machine learning: linear regression and gradient descent
- Metrics and cost functions for machine learning Cross-validation and model selection
- Dimensionality reduction and regularization
- Feature engineering and ensemble models
How does the module work?
The Requirements
This is a true introduction to data science and can accomodate beginners with the right amount of foundational knowledge. It does not require you to have any prior degrees.
To qualify for the course you must have experience with algebraic concepts such as functions and variables, which are frequently used in programming.
Preference is given to applicants with familiarity in programming fundamentals, basic statistics, linear algebra, and calculus.
Students should expect to commit roughly 8 to 10 hours per week between lecture videos, assignments and individual study.
Let’s go!
The module runs four times each calendar year. We strongly encourage all qualified candidates to apply soon, as space in each class is limited and initial interest is high.