Tiêu đề Course Handout-DSA.pdf ✅

[PO.8]. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practices. [PO.9]. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. [PO.10]. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions. [PO.11]. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments. [PO.12]. Life-long learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change. At the end of the program, the students will be able to: [PSO.1] Understand the role of the mathematical, statistical, and AI techniques in the field of data science & engineering. [PSO.2] Apply the acquired knowledge and expertise to perform data analytics tasks for multidimensional data sets. [PSO.3] Develop effective and scalable industrial solutions for real world socio-economic problems using data analytics tools and techniques. D. Assessment Plan: Criteria Description Maximum Marks Internal Assessment (Summative) Continuous Assessments MTE 30 Marks Assignment-10 Marks Quiz-20 Marks 60 Exam (Summative) Exam (Exam) ETE-40 Marks 40 Total 100 Attendance (Formative) A minimum of 75% Attendance is required to be maintained by a student to be qualified for taking up the End Semester examination. The allowance of 25% includes all types of leaves including medical leaves. Make up Assignments (Formative) Students who miss a lab will have to report to the teacher about the absence. A makeup assignment on the topic taught on the day of absence will be given which has to be submitted within a week from the date of absence. No extensions will be given on this. The attendance for that particular day of absence will be marked blank, so that the student is not accounted for absence. These assignments are limited to a maximum of 2 throughout the entire semester.
E. SYLLABUS Introduction: Algorithm Specification; Performance Analysis: Time and Space Complexity, Asymptotic Notation; C Concepts: Pointers, Functions, Arrays, Passing Arrays to Functions through Pointers, Dynamic Memory Allocation, Bubble Sort, Insertion Sort, Selection Sort, Structures, Arrays of Structures, Passing Structures to Functions; List: ADT, Array and its Types, Implementation, Operations, Linked List and its Types, Implementation and Operations; Stack: ADT, Implementations using Array and Linked List, Operations and its Applications; Queue: ADT, Implementations using Array and Linked List, Operations and its Applications; Tree: Terminologies, Different Types, Representation of Binary Tree using Array and Linked Structure, Binary Search Tree, Different Operations (Recursive and Non-Recursive), Heap, Heap Sort, Priority Queue, AVL Trees, B-Tree; Graph: Introduction, Representation, Operations and Applications; Searching Techniques And Hashing. Textbooks: 1. Aaron M. Tenenbaum, Yedidyah Langsam, Moshe J. Augenstein, “Data Structures using C”, Pearson Education, 2013. References Books: 1. Ellis Horowitz, Sartaj Sahni and Susan Anderson-Freed, “Fundamentals of Data Structures in C”, University Press (India) Pvt. Ltd., 2014. 2. Alfred V. Aho, John E. Hopcroft and Jeffrey D. Ullman, “Data Structures and Algorithms”, Pearson Education, 2012. 3. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, “Introduction to algorithms”, PHI, Fourth Edition, 2022. 4. Seymour Lipschutz, “Data Structures with C (Schaum's Outline Series)”, McGraw Hill Education Private Limited, 2011. 5. Mark Allen Weiss, “Data structures and Algorithm Analysis in C”, Pearson, Second edition, 2014. F. Lecture Plan: Class 1. Numbe r Topics Session Outcome Mode of Deliver y Correspon ding Course Outcome Mode of Assessing the Outcome 1. Introduction: Algorithm Specification; define data structure and list various data structure. Lecture DSE 2101.1 Class Quiz MTE, End Term, Home Assignment 2. Performance Analysis: Time and Space Complexity, Asymptotic Notation; analyze time complexity of simple algorithms. Lecture DSE 2101.1 Class Quiz MTE, End Term, Home Assignment 3. C Concepts: Pointers, Functions illustrate pointers in solving problems requiring list of values. Lecture DSE 2101.1 Class Quiz MTE, End Term, Home Assignment 4. C Concepts: Functions Define Array and passing of array through functions and pointers Lecture DSE 2101.1 Class Quiz MTE, End Term,