
Advanced Programming Course
Take your programming career to the next level with a curriculum built for engineers who are serious about writing production-grade code. From data structures and system design to concurrency and security, every topic is grounded in real-world application. This course gives you the technical depth and professional skills that senior engineering roles demand.
What you will learn:
You will master advanced data structures, algorithm design, and object-oriented principles that form the backbone of scalable software. You will apply functional programming techniques, concurrency patterns, and async workflows to build high-throughput systems. The course covers software architecture, API design, and database access patterns for building maintainable services at scale. You will also develop comprehensive testing strategies, performance optimization workflows, and secure coding practices. Supplementary modules address DevOps pipelines, cloud-native architecture, data engineering, and ML model integration, rounding out a complete senior-engineer skill set.
How you study in practice Advanced Programming Course
How you practice Advanced Programming Course
For companies looking to train their teams
With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.
Course Content
8 Chapters • 38 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsProgramming Foundations and Environment Setup
Programming Foundations and Environment Setup
Lesson 1 • Version Control with Git
Introduces Git workflows essential for collaborative and solo advanced projects. Students commit, branch, and merge confidently by section end.
Lesson 2 • Core Programming Concepts Review
Revisits variables, data types, and operators as the baseline for advanced work. Ensures uniform conceptual grounding before introducing complex patterns.
Lesson 3 • Control Flow and Error Handling
Examines conditionals, loops, and structured exception handling as building blocks for robust programs. Connects directly to defensive coding practices used throughout the course.
Lesson 4 • Development Environment Configuration
Covers IDE selection, plugin ecosystems, and environment variables. A properly tuned environment accelerates every subsequent coding task in the course.
Chapter 2HideHide detailsSee detailsData Structures and Algorithm Design
Data Structures and Algorithm Design
Lesson 1 • Non-Linear Data Structures
Explores trees, heaps, and graphs as structures for hierarchical and relational data. Students implement traversal and search algorithms on each structure.
Lesson 2 • Linear Data Structures
Covers arrays, linked lists, stacks, and queues with implementation trade-offs. Provides the structural vocabulary needed for all subsequent algorithm work.
Lesson 3 • Hash Tables and Collision Resolution
Examines hash function design and collision strategies for O(1) average-case lookups. Connects to real-world caching and indexing scenarios introduced later.
Lesson 4 • Algorithm Complexity Analysis
Teaches Big-O, Big-Theta, and Big-Omega notation for rigorous performance reasoning. Students annotate their own code with complexity proofs.
Lesson 5 • Sorting and Searching Algorithms
Analyzes comparison-based and non-comparison sorting alongside binary search variants. Students benchmark implementations to internalize time-space trade-offs.
Chapter 3HideHide detailsSee detailsObject-Oriented Design Principles
Object-Oriented Design Principles
Lesson 1 • Design Patterns: Creational
Covers Factory, Builder, Singleton, and Prototype patterns with use-case rationale. Students implement each pattern and identify misuse anti-patterns.
Lesson 2 • Design Patterns: Structural and Behavioral
Examines Adapter, Decorator, Observer, and Strategy patterns as solutions to recurring design problems. Students select patterns based on change-axis analysis.
Lesson 3 • SOLID Principles in Practice
Applies each SOLID principle to realistic code samples with before-and-after comparisons. Builds the judgment needed to evaluate design quality in code reviews.
Lesson 4 • Encapsulation and Abstraction
Defines information hiding and interface-based design as tools for reducing coupling. Students redesign leaky APIs to enforce proper access boundaries.
Lesson 5 • Inheritance and Polymorphism
Contrasts classical inheritance with composition and explains runtime polymorphism. Students identify when inheritance creates fragility and refactor accordingly.
Chapter 4HideHide detailsSee detailsFunctional Programming Techniques
Functional Programming Techniques
Lesson 1 • Monads and Functional Error Handling
Introduces Maybe, Either, and Result types as composable error-handling abstractions. Students replace nested null checks with monadic pipelines.
Lesson 2 • Closures and Lexical Scope
Explains how closures capture environment and enable stateful functional patterns. Students debug common closure pitfalls in loop and async contexts.
Lesson 3 • Higher-Order Functions
Covers map, filter, reduce, and function composition as primary data-transformation tools. Connects to pipeline architectures introduced in later chapters.
Lesson 4 • Pure Functions and Immutability
Defines referential transparency and side-effect isolation as the foundation of functional style. Students audit existing code for hidden state mutations.
Chapter 5HideHide detailsSee detailsConcurrency and Asynchronous Programming
Concurrency and Asynchronous Programming
Lesson 1 • Reactive and Event-Driven Patterns
Introduces observable streams and backpressure as tools for composable async workflows. Students build a reactive pipeline handling variable-rate data sources.
Lesson 2 • Concurrent Data Structures
Examines lock-free queues, concurrent hash maps, and atomic operations for contention reduction. Connects to high-performance service design in later chapters.
Lesson 3 • Async/Await and Promises
Teaches promise chaining and async/await syntax for non-blocking I/O operations. Students convert callback-heavy code to clean async pipelines.
Lesson 4 • Threads and Process Models
Contrasts thread-based and process-based concurrency with scheduling implications. Establishes the mental model needed for all subsequent concurrency topics.
Lesson 5 • Synchronization Primitives
Covers mutexes, semaphores, and read-write locks for safe shared-state access. Students reproduce and then fix classic race conditions in lab exercises.
Chapter 6HideHide detailsSee detailsSoftware Architecture and System Design
Software Architecture and System Design
Lesson 1 • Scalability and Reliability Patterns
Teaches load balancing, circuit breakers, and bulkhead isolation for fault-tolerant services. Students apply patterns to a reference architecture under simulated failure.
Lesson 2 • Architecture Decision Records
Formalizes the process of documenting design choices with context, options, and consequences. Students produce ADRs for every major decision in their capstone project.
Lesson 3 • API Design and Contract-First Development
Covers RESTful principles, GraphQL schemas, and gRPC contracts as interface design tools. Students write API specifications before implementation to enforce contract discipline.
Lesson 4 • Architectural Styles Overview
Surveys monolithic, layered, microservices, and event-driven styles with trade-off matrices. Provides the vocabulary for all subsequent design decisions in the course.
Lesson 5 • Database Design and Access Patterns
Examines relational normalization, NoSQL data modeling, and query optimization for diverse workloads. Students choose storage engines based on access-pattern analysis.
Chapter 7HideHide detailsSee detailsTesting, Debugging, and Code Quality
Testing, Debugging, and Code Quality
Lesson 1 • Static Analysis and Code Review
Applies linters, type checkers, and structured review checklists to enforce quality gates. Students conduct peer reviews using a rubric derived from SOLID principles.
Lesson 2 • Performance and Load Testing
Introduces profiling, benchmarking, and load simulation to identify bottlenecks before production. Students correlate profiler output with architectural decisions.
Lesson 3 • Integration and End-to-End Testing
Covers contract testing, database integration tests, and UI automation for full-stack validation. Students design a test pyramid balancing speed and confidence.
Lesson 4 • Unit Testing Fundamentals
Establishes test structure, assertion libraries, and the Arrange-Act-Assert pattern for isolated tests. Students retrofit tests onto legacy code using dependency injection.
Lesson 5 • Test-Driven Development
Applies the red-green-refactor cycle to drive design from failing tests. Students build a feature end-to-end using strict TDD discipline.
Chapter 8HideHide detailsSee detailsPerformance Optimization and Advanced Patterns
Performance Optimization and Advanced Patterns
Lesson 1 • Memory Management and Optimization
Examines garbage collection tuning, object pooling, and memory leak detection for low-latency systems. Students reduce heap allocation in a provided high-throughput service.
Lesson 2 • Advanced Design Patterns
Introduces CQRS, event sourcing, and saga patterns for complex domain and distributed scenarios. Students implement an event-sourced aggregate with full replay capability.
Lesson 3 • Parallel and Distributed Computing
Applies data parallelism, task parallelism, and MapReduce patterns to large-scale computation. Students partition a batch job across worker nodes and measure speedup.
Lesson 4 • Caching Strategies
Covers in-process, distributed, and CDN caching with invalidation policies for each tier. Students implement a multi-tier cache and measure hit-rate improvements.
Lesson 5 • Profiling-Driven Optimization Workflow
Establishes a repeatable measure-analyze-optimize loop grounded in empirical data. Students apply the workflow to their capstone project and document gains.
Your valid completion certificate
This course is for you:
Mid-level developer: ready to move beyond feature work into system ownership.
Computer science graduate: bridging the gap between academic theory and industry practice.
Self-taught programmer: filling critical knowledge gaps that tutorials never addressed.
Backend engineer: seeking the architecture and design depth that promotions require.
Career changer: bringing domain expertise and now building serious engineering foundations.
DevOps practitioner: expanding into software design to collaborate more effectively with developers.
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