Library load in Python
Help in Python
Interpreting error messages
N-dimensional arrangements
NumPy array manipulation
Computation on NumPy arrays: built-in functions
Boolean comparisons, masks and statements
Reading and writing files with NumPy
Troubleshooting with SciPy
◦ Linear algebra
◦ Integration
◦ Statistics
◦ Scattered matrices
Data manipulation with Pandas
◦ Introduction to Pandas objects
◦ Dataframes
◦ Manipulation of objects
◦ Missing data handling
◦ Aggregation and grouping
◦ Time series
Visualization with Matplotlib
◦ Creating charts displaying the error
◦ Subgraphs
◦ Personalization
Parallel programming with MPI4Py
◦ Parallel paradigm with message passing
◦ Decomposition of the domain
◦ Point-to-point communications
◦ Collective communications
Final practice