Geared for data scientists and engineers with potentially light practical programming background or experience, this course provides a ramp-up to using Python for scientific and mathematical computing. Students will explore basic Python scripting and concepts, and then move to the most important Python modules for working with data, from arrays to statistics to plotting results. Throughout the course you will learn to write essential Python scripts and apply them within a scientific framework working with the latest technologies.
Join an engaging hands-on learning environment, where youÆll:
- Create and run basic programs
- Design and code modules and classes
- Implement and run unit tests
- Use benchmarks and profiling to speed up programs
- Process XML and JSON
- Manipulate arrays with NumPy
- Get a grasp of the diversity of subpackages that make up SciPy
- Use iPython notebooks for ad hoc calculations, plots, and what-if?
- Manipulate images with PIL
- Solve equations with SymPy
This course has a 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work.
Data Scientist, Data Analyst, Data Engineer, or anyone tasked with utilizing Python for data analytics actions.