Module | Important Topics |
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Programming Fundamentals | Introduction to Programming, Data Types, Control Structures, Functions, Arrays |
Data Structures and Algorithms | Arrays, Stacks, Queues, Linked Lists, Trees, Graphs, Sorting and Searching Algorithms |
Database Management Systems | ER Models, SQL, Normalization, Transactions, Concurrency Control, Indexing and Hashing |
Operating Systems | Processes, Threads, Scheduling, Synchronization, Deadlocks, Memory Management |
Mathematics for Data Science | Linear Algebra, Calculus, Statistics, Probability, Discrete Mathematics |
Data Science Fundamentals | Data Preprocessing, Exploratory Data Analysis, Visualization, Introduction to Machine Learning |
Machine Learning | Supervised Learning, Unsupervised Learning, Reinforcement Learning, Model Evaluation |
Deep Learning | Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, TensorFlow and Keras |
Big Data Technologies | Hadoop, Spark, Hive, Pig, NoSQL Databases |
Capstone Project | Application of Data Science and Machine Learning techniques to solve real-world problems |