Course Overview:
This course introduces learners to problem-solving, logical thinking, and algorithm design using the Go programming language. It covers core data structures and algorithms, implemented step-by-step using Go syntax and best practices. This course is ideal for students, backend developers, and those preparing for coding interviews or system-level programming.
Way of Training:
- Mode: Online / Offline
- Duration: 45 Days
- Online Sessions: 1 Hour/Day
- Offline Sessions: 1 Hour Theory + 1 Hour Lab/Practical
Data Structures and Algorithms Using Go (Golang)
Course Fee:
- Online Mode: 3999/- only
- Offline Mode: 4999/- only
Includes:
- Live or recorded sessions
- Full programs with dry-run explanation
- Notes, worksheets, and problem sets
- Mini project using DSA in Go
- Interview Q&A and competitive coding practice
- Telegram/WhatsApp group for support
Instructor Video :
About the Course:
Golang is known for its performance, concurrency, and clean syntax. This course uses Go to implement key data structures like arrays, linked lists, trees, graphs, and advanced algorithms like recursion, greedy, and dynamic programming. It also gives a practical introduction to Go syntax and packages.
Job Roles After Learning Go with DSA:
- Golang Backend Developer
- Software Engineer with strong algorithm skills
- DevOps and Systems Programming roles
- Backend Microservices Developer
- Placement-ready college student
Importance of DSA in Golang:
- Boosts performance in backend systems
- Used in algorithm-based company tests
- Essential for technical interviews
- Golang makes data handling efficient
- Helps in understanding memory, pointers, and concurrency
Course Content
Module 1: Go Language Recap + DSA Overview
- Basic syntax and structure of Go
- Variables, functions, arrays, slices, structs
- Why data structures and where to use
- Time and space complexity
- Big O, Big Theta, Big Omega explained with examples
- Tracing examples using print/logging
Module 2: Arrays and Linear Search
- Arrays and slices
- Insert, delete, search, update
- Linear Search with dry-run
- Mini program: Manage attendance using array
- Slice operations and capacity expansion
Module 3: Binary Search and Sorting
- Binary Search implementation
- Bubble sort, Insertion sort, Selection sort
- Merge sort and Quick sort using recursion
- Comparison of sorting algorithms
- Mini Task: Sort employee slice by name or salary
Module 4: Strings and Runes
- String declaration and traversal using runes
- Reverse, count characters, check palindrome
- Custom string operations without libraries
- Mini Task: Remove duplicate characters from a string
Module 5: Recursion in Go
- What is recursion, how stack is used
- Factorial, Fibonacci, power of a number
- Dry-run using recursive tree
- Backtracking basics
- Mini Program: Subset generation using recursion
Module 6: Stack
- Stack using slice
- Push, Pop, Peek, IsEmpty operations
- Balanced parentheses checker
- Postfix expression evaluation
- Mini Project: Undo-Redo text editor simulation
Module 7: Queue and Circular Queue
- Queue using slice and struct
- Operations: Enqueue, Dequeue, Peek
- Circular Queue logic
- Double-Ended Queue using slice
- Mini Task: Print Job queue simulator
Module 8: Linked Lists
- Singly linked list using struct
- Insert at beginning, end, middle
- Delete and search nodes
- Doubly linked list basics
- Mini Program: Playlist manager using linked list
Module 9: Trees
- Binary Tree and Binary Search Tree
- Traversal: Inorder, Preorder, Postorder
- Insert, Search, Delete in BST
- Leaf nodes, height, and mirror tree
- Mini Project: Organization hierarchy tree
Module 10: Graphs
- Adjacency list using map of slices
- DFS and BFS
- Shortest path using BFS
- Cycle detection in graph
- Mini Program: City road network simulation
Module 11: Maps and Hashing
- Maps in Go for key-value storage
- Hashing logic using map
- Collision handling (chaining logic using slice of structs)
- Mini Project: Phonebook using maps
Module 12: Greedy Algorithms
- Activity selection
- Minimum coin problem
- Fractional knapsack
- Job scheduling with deadlines
- Dry-run each step with logging
Module 13: Dynamic Programming
- Tabulation and Memoization using maps and slices
- Fibonacci using DP
- 0/1 Knapsack problem
- Longest Common Subsequence (LCS)
- Mini Project: Game score optimizer using DP
Module 14: Mini Project in Go (CLI-based)
- Project Title: Student Report Manager
- Add, delete, search, sort students
- Search by roll number or name
- Sort by percentage or name
- Uses arrays, maps, and file I/O
- Command-line interface using bufio.Scanner
Top 10 Interview Questions
- What is the difference between array and slice in Go?
- How does map work internally in Golang?
- How do you implement recursion in Go?
- What are the common use cases for stack and queue?
- How is DFS different from BFS in graph traversal?
- What is the difference between struct and class in Go?
- Explain how hash table can be implemented in Go.
- What is the time complexity of merge sort and quick sort?
- What is dynamic programming and how do you apply it?
- How can you sort custom structs in Go?
Why Join Techidz for Go DSA?
- Beginner-friendly explanation in simple Go syntax
- 100+ hands-on examples and mini programs
- Step-by-step recursion and sorting dry-runs
- Real-time Go data structures using structs and slices
- Strong preparation for interviews and backend jobs
- Complete notes, code, video access, and support
New & Special Features in Techidz Golang DSA Course
- Live classes with practical trace
- DSA + Golang combined skill set
- Mini project using file operations and slices
- Worksheet-based practice
- Interview Q&A with competitive problems
- Lifetime access to all content and Telegram group
