Course overview
Introduces fundamental concepts of building data science applications in Python. Object oriented fundamentals x001A 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
- Apply good programming style and understand the impact of style on developing and maintaining programs
- Effectively use a version control system and the Linux command-line tools for incremental development
- Implement, test and debug solutions in Python
- Identify the relative merits of different algorithmic designs
- Analyse algorithms and identify key algorithmic strategies
- Explain fundamental computing algorithms