Explores the practical application of language theory, including quicksort, gradual typing, and efficient memory management, as well as the challenges of reduction program synthesis.
Introduces records, variants, evaluation rules, typing rules, aliasing challenges, and benefits in programming languages.
Covers algorithmic thinking, Python programming, numerical methods, and essential computing concepts for scientific computing.
Introduces algorithms as problem-solving procedures, covering complexity, correctness, and implementation in various languages.
Delves into advanced Spark optimization techniques, emphasizing data partitioning, shuffle operations, and memory management.
Covers the efficiency of register machines over stack machines, memory organization, and mapping instructions.
Explores programming language security, covering type safety, memory safety, threat safety, Rust's ownership model, sandboxing, and compartmentalization.
Offers a crash course in MATLAB, covering data representation, array indexing, mathematical operations, and common pitfalls.
