اپلیکیشن اندرویدی فلش‌کارت آموزشی آمادگی برای مصاحبه‌های فنی و کدینگ (Technical/Coding Interview)

🎓 دوره آموزشی جامع

📚 اطلاعات دوره

عنوان دوره: دوره آمادگی برای مصاحبه‌های فنی و کدینگ (Technical/Coding Interview)

موضوع کلی: آموزش زبان‌های خارجی

موضوع میانی: زبان برای مصاحبه شغلی

📋 سرفصل‌های دوره

• 1. Introduction to Technical Interviews: Types and Expectations
• 2. The Role of Language Proficiency in Tech Interviews
• 3. Defining Your Career Goals and Interview Strategy
• 4. Crafting an Impactful Resume: Content and Language
• 5. Writing a Targeted Cover Letter (Optional but Recommended)
• 6. Navigating Job Boards and Professional Networking
• 7. Deconstructing Job Descriptions and Requirements
• 8. Mastering Different Interview Formats (Phone, Video, On-site)
• 9. First Impressions: Professional Greetings and Small Talk (Language Focus)
• 10. The "Tell Me About Yourself" Question: Structure and Delivery
• 11. Asking Insightful Questions to Your Interviewer
• 12. Enhancing Active Listening and Comprehension Skills
• 13. Non-Verbal Communication and Body Language in Interviews
• 14. Strategies for Managing Interview Anxiety and Pressure
• 15. Post-Interview Follow-up: Thank You Notes and Next Steps
• 16. Core Programming Concepts: Variables, Data Types, Operators
• 17. Control Flow: Conditional Statements (If/Else, Switch)
• 18. Control Flow: Loops (For, While, Do-While)
• 19. Functions and Methods: Definition, Parameters, Return Values
• 20. Introduction to Object-Oriented Programming (OOP) Principles
• 21. OOP: Classes and Objects in Detail
• 22. OOP: Encapsulation and Abstraction
• 23. OOP: Inheritance and Polymorphism
• 24. Error Handling and Exception Management Best Practices
• 25. Debugging Techniques for Interview Problems
• 26. Understanding Memory Management Basics
• 27. Introduction to Time and Space Complexity (Big O Notation)
• 28. Analyzing Best, Average, and Worst-Case Scenarios
• 29. Expressing Technical Concepts Clearly in a Foreign Language
• 30. Essential Programming Vocabulary for Interviews
• 31. Arrays: Fixed-Size Collections and Basic Operations
• 32. Strings: Manipulation, Palindromes, and Anagrams
• 33. Linked Lists: Singly, Doubly, and Circular Structures
• 34. Linked Lists Operations: Insertion, Deletion, Reversal
• 35. Stacks: LIFO Principle and Applications (e.g., Parentheses Matching)
• 36. Queues: FIFO Principle and Applications (e.g., BFS)
• 37. Hash Tables: Key-Value Pairs, Hashing Functions
• 38. Hash Collisions and Resolution Strategies
• 39. Applications of Hash Maps and Hash Sets
• 40. Trees: Basic Terminology and Types
• 41. Binary Trees: Properties and Common Operations
• 42. Tree Traversal: Pre-order, In-order, Post-order
• 43. Binary Search Trees (BSTs): Properties and Operations
• 44. AVL Trees and Red-Black Trees (Introduction)
• 45. Heaps: Min-Heap, Max-Heap, and Heapify Process
• 46. Priority Queues: Implementation using Heaps
• 47. Graphs: Vertices, Edges, Directed/Undirected Graphs
• 48. Graph Representations: Adjacency Matrix vs. Adjacency List
• 49. Disjoint Set Union (DSU) / Union-Find Algorithm
• 50. Tries (Prefix Trees) for String Operations
• 51. Fenwick Tree (Binary Indexed Tree) for Range Queries
• 52. Segment Tree for Range Queries and Updates
• 53. Choosing the Right Data Structure for a Problem
• 54. Articulating Data Structure Pros and Cons (Language Focus)
• 55. Technical Vocabulary: Data Structures
• 56. Sorting Algorithms: Bubble, Selection, Insertion Sort
• 57. Sorting Algorithms: Merge Sort (Divide and Conquer)
• 58. Sorting Algorithms: Quick Sort (Partitioning)
• 59. Searching Algorithms: Linear Search vs. Binary Search
• 60. Recursion: Base Cases, Recursive Steps, Stack Overflow
• 61. Backtracking Algorithms (e.g., N-Queens, Sudoku Solver)
• 62. Dynamic Programming: Introduction to Memoization
• 63. Dynamic Programming: Tabulation and State Transitions
• 64. Common DP Problems: Knapsack, Longest Common Subsequence
• 65. Greedy Algorithms: Characteristics and Applications
• 66. Graph Traversal: Breadth-First Search (BFS)
• 67. Graph Traversal: Depth-First Search (DFS)
• 68. Shortest Path Algorithms: Dijkstra's Algorithm
• 69. Shortest Path Algorithms: Bellman-Ford Algorithm (Negative Weights)
• 70. Minimum Spanning Tree: Prim's Algorithm
• 71. Minimum Spanning Tree: Kruskal's Algorithm
• 72. Topological Sort for Directed Acyclic Graphs (DAGs)
• 73. Bit Manipulation: Operators and Techniques
• 74. Sliding Window Technique for Subarray/Substring Problems
• 75. Two Pointers Technique for Array Problems
• 76. Developing an Algorithm: Understanding and Clarifying the Problem
• 77. Brainstorming Multiple Approaches and Trade-offs (Language Focus)
• 78. Explaining Your Algorithm Logic Step-by-Step (Language Focus)
• 79. Optimizing Algorithms: Time and Space Complexity Analysis
• 80. Technical Vocabulary: Algorithms
• 81. Introduction to System Design Interviews: Goals and Process
• 82. Fundamental Design Principles: Scalability, Reliability, Maintainability
• 83. Scaling Strategies: Horizontal vs. Vertical Scaling
• 84. Load Balancing Techniques and Implementations
• 85. Database Choices: SQL, NoSQL, and Hybrid Approaches
• 86. Caching Mechanisms: Strategies and Invalidation
• 87. Message Queues and Asynchronous Processing Patterns
• 88. Designing APIs: RESTful Principles, GraphQL, gRPC
• 89. Microservices Architecture: Advantages and Challenges
• 90. Designing for High Availability and Fault Tolerance
• 91. Security Considerations in System Design
• 92. Data Partitioning and Replication Strategies
• 93. Capacity Estimation and Performance Metrics
• 94. Presenting Your System Design Solution Clearly (Language Focus)
• 95. Discussing Trade-offs and Justifying Decisions (Language Focus)
• 96. Mastering Behavioral Questions: The STAR Method (Language Focus)
• 97. Discussing Teamwork, Collaboration, and Conflict Resolution
• 98. Articulating Strengths, Weaknesses, and Learning Experiences
• 99. Realistic Mock Interview Simulation and Peer Feedback
• 100. Final Preparation: Review, Confidence, and Continuous Improvement