Course overview
Introduces fundamental concepts of building data science applications in Python. Object oriented fundamentals methods, and classes. Algorithms and problem solving - problem solving processes and strategies. Computational complexity of algorithms. Software development tools and techniques - testing: black box, requirements. Representation and manipulation of large scale data sets.
Course learning outcomes
- Evaluate real world problems and data and translate to computer representation.
- Demonstrate practical ability to use Python prediction and classification tools.
- Demonstrate ability to construct complex Python programs.
- Interpret and express the language of data science and programming.