Data structures and algorithms course objectives
- To equip students with the knowledge and skills to efficiently organize, manage, and process data.
- Teach students how to select and implement appropriate data structures, such as arrays, linked lists, trees, and graphs, to optimize data access and manipulation.
- It also focuses on developing algorithms for sorting, searching, and other computational tasks to enhance problem-solving capabilities.
- Participants can improve their programming efficiency, prepare for technical interviews, and build a strong foundation for advanced computer science studies.
The course highlights why data structures and algorithms course in VyTCDC?
- The Data Structures and Algorithms course provides a comprehensive understanding of essential concepts, their importance, and classification. It delves into the implementation, operations, and use cases of various data structures, ensuring a solid foundation in their practical applications. The course covers the principles, applications, and implementation techniques of stacks and queues, crucial for efficient data management.
- Participants will explore binary trees, binary search trees, AVL trees, and graph algorithms, gaining insights into their structures and uses. The course also includes hashing techniques, collision resolution, and performance analysis, which are essential for optimizing data retrieval. Sorting and searching algorithms such as bubble sort, merge sort, quick sort, and binary search are thoroughly examined, highlighting their efficiency and application scenarios.
- A significant focus is placed on algorithm analysis, particularly time and space complexity, to understand and improve algorithm performance. The course introduces dynamic programming and greedy algorithms, emphasizing concepts and problem-solving strategies. Advanced data structures, including heaps, tries, and segment trees, are covered to equip students with knowledge of sophisticated data handling techniques.
- A significant focus is placed on algorithm analysis, particularly time and space complexity, to understand and improve algorithm performance. The course introduces dynamic programming and greedy algorithms, emphasizing concepts and problem-solving strategies. Advanced data structures, including heaps, tries, and segment trees, are covered to equip students with knowledge of sophisticated data handling techniques.
Training option available example section
- Classroom-based lectures offer structured learning with direct interaction between instructors and students. This format provides a solid foundation in Data Structures and Algorithms (DSA) through detailed explanations and guided discussions, allowing for immediate clarification of concepts and real-time feedback.
- Hands-on workshops are integral to practical learning. They feature real-time coding practice and problem-solving exercises. These sessions enable students to apply theoretical knowledge to practical scenarios, reinforcing their understanding through active engagement with coding challenges and projects.
- Intensive, short-term courses focus on immersive learning and are designed to build expertise in DSA rapidly. These courses provide an accelerated learning experience through concentrated study and practice, preparing students for technical challenges and competitive programming in a shorter time frame. This approach combines rigorous instruction with practical application to ensure comprehensive skill development.
- The best way to learn data structures and algorithms is through a combination of theoretical study and practical application. Earning data structures and algorithms certification can significantly enhance your understanding and career prospects.
Key features offered by VyTCDC
- The DSA course covers fundamental and advanced data structures such as arrays, linked lists, stacks, queues, trees, graphs, heaps, tries, and segment trees. It provides a detailed exploration of algorithms, including sorting, searching, dynamic programming, and greedy algorithms. The course is taught by instructors with extensive industry experience and strong academic backgrounds in computer science, offering personalized feedback and mentorship. Flexible learning schedules are supported through self-paced modules and live instructor-led sessions, ensuring students can learn data structures and algorithms at their own pace while receiving expert guidance.
FAQ
VyTCDC Instructors have extensive industry experience and strong academic backgrounds in computer science, providing expert guidance and personalized feedback.
VyTCDC offers various formats, including classroom-based lectures, hands-on workshops, self-paced modules, and live instructor-led sessions for flexible learning schedules.
The course includes practical sessions and projects that simulate real-world challenges, enabling you to apply theoretical knowledge to actual coding problems.
Yes, upon successful completion of the course, participants receive industry-recognized certification, which can aid in job placements and career advancement.
To get the most out of the course, basic programming knowledge and familiarity with at least one programming language are recommended.
The course offers job placement assistance, resume building, interview preparation, and networking opportunities to support career advancement.
Yes, you will have access to comprehensive study materials, practice problems, coding challenges, and online libraries to enhance your learning experience.
Course Description
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Key Features:
- Course Duration – 30 Days (4 Hrs. per day)
- Guidance from Technology Expert.
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- CODE-A-THON Racing Session
- Advanced UI/UX Course
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Curriculum
- 5 Sections
- 35 Lessons
- 60 Hours
Expand all sectionsCollapse all sections
- Introduction to Data Structures3
- Basic math operations & Asymptotic analysis4
- Algorithms Fundamentals8
- 1.0Basics of algorithm analysis: Time complexity, space complexity
- 1.1Searching and sorting algorithms: Linear search, binary search, bubble sort, merge sort, quicksort, etc.
- 1.2Recursion and its applications in algorithms
- 1.3Greedy Algorithms
- 1.4Dynamic Programming
- 1.5Naive string searching
- 1.6Divide and Conquer
- 1.7Backtracking
- Data Structures14
- 2.0Linear Data Structures
- 2.1Arrays and dynamic arrays
- 2.2Linked Lists: Singly linked lists, doubly linked lists, circular linked lists
- 2.3Stacks and Queues: Implementation, applications, and use cases
- 2.4Non-Linear Data Structures
- 2.5Trees: Binary trees, binary search trees (BSTs), AVL trees, B-trees
- 2.6Tree traversals, tree dynamic programming
- 2.7Graphs: Representation, traversal algorithms (BFS, DFS)
- 2.8Shortest path algorithms (Dijkstra’s, Bellman-Ford, Floyd-Warshall)
- 2.9Minimum spanning tree (Prim and Kruskal algorithms)
- 2.10Network flow algorithms (Ford-Fulkerson, Edmonds-Karp)
- 2.11Biconnectivity in undirected graphs (bridges, articulation points)
- 2.12Strongly connected components in directed graphs
- 2.13Topological Sorting
- Advanced Data Structures6
Technical Training Director
Chapters:
