My BSc computer science degree

I’m about to finish a bachelor’s degree in computer science at the Technische Universität Berlin. Here’s what I’ve learned in the courses:

Course	Type	Topics
Computer architecture	Mandatory	CPU design, FPU, Caches, Pipelining, Machine code, Assembly, MIPS
Introduction to programming	Mandatory	C, Algorithm basics
Computer science propaedeutic	Mandatory	Basics
Formal languages and automatons	Mandatory	State machines, Propositional logic, Chomsky hierarchy
Analysis I for engineers	Mandatory	Complex numbers, Convergence, Functions, Differentiation, Integration, Fourier analysis, Infinite series
Systems programming	Mandatory	C, Processes, Threads, Scheduling, Parallelization, Mutexes, Memory
Algorithms and data structures	Mandatory	Java, OOP, Graph theory, Dynamic programming
Information systems and data analysis	Mandatory	SQL, ER diagrams, Relational database design, Relational algebra
Computability and complexity	Mandatory	Turing machines, Decidability, Halting problem, Complexity classes (P vs. NP)
Linear algebra for engineers	Mandatory	Vectors, Matrices, Linear mappings
Computer networks and distributed systems	Mandatory	DNS, WWW, OSI layers, NTP, Pub–Sub
Software techniques and programming paradigms	Mandatory	Requirements engineering, Correctness, Testing, Code quality, UML, Functional programming, Logical programming, Haskell, Prolog, C, Java
Scientific computing	Mandatory	Python, Numerical analysis, Numerical approximation and error, Regression, SVD, Interpolation, DFT, FFT, Optimization
Logic	Mandatory	Predicate logic, Normalization, Resolution, Satisfiability problem, Sequent calculus, Models and structures, Finite games
Discrete structures	Mandatory	Combinatorics, Principle of inclusion and exclusion, Permutations, Partitioning, Recursion, Number theory, Modular arithmetic, Graph theory
Stochastics for computer science	Mandatory	Probability theory, Random variables, Distributions, Markov chains, Central limit theorem, Hypothesis tests
Information governance	Mandatory	Scientific and technical writing, Big Data, eCommerce, Privacy
Digital systems	⭐ Elective-compulsory	Boolean algebra, CMOS, Logic gates, Number encoding, Circuits
Programming practical coutse: cyber-physical systems	⭐ Elective-compulsory	JavaScript, HTML, CSS, Client and server, Node.js, Express.js, Teamwork
Principles of algorithmics	⭐ Elective-compulsory	Algorithmics
Web technologies	⭐ Elective-compulsory	HTML, CSS, JavaScript, jQuery, Bootstrap, Node.js, Express.js, Client–Server, SPA
Cognitive algorithms	⭐ Elective-compulsory	Machine learning, Gradients, Perceptron, NNs, PCA, OLS, KPCA, LDA, MLP
Python for machine learning	⭐ Elective-compulsory	Python, machine learning, Numpy, MatPlotLib, Linear algebra, Regression, Cython
Principles of information security	⭐ Elective-compulsory	Social engineering, Information security management systems, authentication and authorization, CIA, Standards, PKIs
Usability engineering	⭐ Elective-compulsory	Quality engineering, Perception psychology, Human factors, Media systems, Audio and video quality, Video game network considerations, System design, Experiment design
Database seminar: foundations of database systems	⭐ Elective-compulsory	Query processing, Presenting, Scientific and technical writing, LaTeX, SQL, Data Warehousing, Transaction management, Parallelism in database systems
Computer graphics	⭐ Elective-compulsory	TypeScript, THREE.js, OpenGL, WebGL, GLSL, Perspective geometry and projection, Clipping and culling, Shading and ligting, Texturing, Rasterization, Ray casting, Radiosity, Color theory, Image encoding
Bachelor’s thesis	⭐ Elective-compulsory	DNS-based Authentication of Named Entities (DANE) TLSA, TLS, RSA, Security, DNS, DNSSEC, OpenSSL, Identity management
LaTeX introduction	🌟 Optional	LaTeX, Typesetting, Packages, Editors, Distributions, Compilation, Document structure
Data science toolbox	🌟 Optional	Java, Crawling, Machine learning basics, visualization
Intellectual property law	🌟 Optional	Copyright, Software distribution, Brands, Patents