| S.NO | YEAR/SEMESTER | COURSE CODE & TITLE | UNIT | TOPIC | INNOVATIVE TEACHING METHOD USED |
| 1 | II/III | MA3354 DISCRETE MATHEMATICS | 1 | Tautology and Contradiction | FCS |
| Inference Theory | FCS |
| Proof methods and strategy | Z-A Approach |
| 2 | Strong induction and well ordering | Flipped classroom |
| Recurrence relations | Flipped classroom |
| Inclusion and exclusion principle and its applications | Think Pair Share |
| 3 | Graphs and graph models | Flipped classroom |
| Graph terminology and special types ofgraphs | Think Pair Share |
| Matrix representation of graphs andgraph isomorphism | Flipped classroom |
| 4 | Subgroups | Think Pair Share |
| Normal subgroup and cosets | Flipped classroom |
| 5 | Properties of lattices | Flipped classroom |
| Lattices as algebraic systems | MIND MAPPING |
| Direct product and homomorphism | Flipped classroom |
| 2 | II/III | CS3351 DIGITAL PRINCIPLES AND COMPUTER ORGANIZATION | 1 | Analysis and Design Procedures | Z-A approach |
| Magnitude Comparator | Flipped Classroom |
| Encoder | Flipped Classroom |
| 2 | Operation and excitation tables,Triggering of FF | Flipped Class Room |
| State minimization, stateassignment | Flipped Class Room |
| Counters | Z-A technique |
| 3 | Functional Units of a DigitalComputer: Von NeumannArchitecture | Think-Pair-share |
| Addressing Modes | Flipped Classroom |
| Interaction between Assemblyand High-Level Language | Flipped Classroom |
| 4 | Micro programmed Control | Flipped Classroom |
| Data Hazard | Z-A approach |
| Control Hazards | Flipped Classroom |
| 5 | Memory Concepts andHierarchy | Flipped Classroom |
| DMA | Think-Pair-Share |
| Interconnection Standards:USB, SATA | Flipped Classroom |
| 3 | II/III | AD3391 DATABASE DESIGN AND MANAGEMENT | 1 | Requirements collection | Flipped Classroom |
| Entity-Relationship model | Think Pair Share |
| UML class diagrams | Flipped Classroom |
| 2 | Relational model concepts. | Flipped Classroom |
| SQL Data manipulation | Flipped Classroom |
| Views–SQL programming | JIGSAW |
| 3 | ER and EER-to-Relationalmapping | Z-A Approach |
| Minimal cover | Flipped Classroom |
| Properties of relationaldecomposition | Flipped Classroom |
| 4 | Transaction concepts – properties | Think Pair Share |
| Two-phase locking techniques. | Flipped Classroom |
| Serializability | Flipped Classroom |
| 5 | Object identifier – referencetypes – row types – | Flipped Classroom |
| UDTs – Subtypes andsupertypes – user-definedroutines – | Z-A Approach |
| No-SQL: | Flipped Classroom |
| 4 | II/III | AL3391 ARTIFICIAL INTELLIGENCE | 1 | Concept of Rationality | Flipped Classroom |
| Structure of agents | Think Pair Share |
| Uninformed strategies | Flipped Classroom |
| 2 | Heuristic functions | Flipped Classroom |
| Local search in continuous space | Flipped Classroom |
| Online search | Think Pair Share |
| 3 | Alpha-beta search | Flipped Classroom |
| Monte-Carlo tree search | Z-A Approach |
| Constraint propagation | Flipped Classroom |
| 4 | Propositional logic | Think Pair Share |
| Propositional model checking | Flipped Classroom |
| Knowledge representation andengineering | Flipped Classroom |
| 5 | Naïve Bayes models | Flipped Classroom |
| Probabilistic reasoning | Z-A Approach |
| Exact inference | Flipped Classroom |
| 5 | II/III | AD3351 DESIGN AND ANALYSIS OF ALGORITHMS | 1 | Fundamentals of AlgorithmicProblem Solving | Flipped Class Room |
| Mathematical analysis forNon-recursive & recursivealgorithms | Flipped Class Room |
| Empirical analysis of Algorithm | Flipped Class room |
| 2 | Multiplication of Large, Integers – Strassen’sMatrix Multiplication | Flipped Class Room |
| Closest-Pair and Convex-Hull Problems | Flipped Class Room |
| Quick sort | Role Play |
| 3 | Dynamic programming- Principleof optimality Coin changingproblem | Flipped Class Room |
| Dijistra’s algorithm | Flipped Class Room |
| 4 | Maximum Matching in BipartiteGraphs | Flipped Class Room |
| Algorithm for MaximumMatching in Bipartite Graphs | Think – Pair – Share |
| The stable marriage problem | Flipped Class Room |
| 5 | Backtracking – nQueens problem | Flipped Class Room |
| Traveling Salesman Problem | Mind Mapping |
| Traveling Salesmanproblem – Knapsack problem | Flipped Class Room |
| 6 | II/III | AD3301 DATA EXPLORATION AND VISUALIZATION | 1 | Significance of EDA, Makingsense of data | Mind Mapping |
| Comparing EDA with classical and Bayesian analysis, Softwaretools for EDA | Flipped Class Room |
| Merging Database | Flipped Class Room |
| 2 | Simple line plots – Simplescatter plots | Flipped Class Room |
| Visualizing errors – densityAnd contour plots | Flipped Class Room |
| Colors – subplots – text andannotation | Mind Mapping |
| 3 | Distributions and Variables | Flipped Class Room |
| Numerical Summaries of Leve | Flipped Class Room |
| Scaling | Mind Mapping |
| 4 | Relationships between TwoVariables | Flipped Class Room |
| Percentage Tables | Flipped Class Room |
| Contingency Tables | Mind Mapping |
| 5 | Causal Explanations | Flipped Class Room |
| Longitudinal Data | Z-A Approach |
| Three-Variable ContingencyTables and Beyond | Flipped Class Room |