INTRODUCTION TO DATA SCIENCE

Day 1: What is Data Science, Applications of Data Science, Python Libraries for Data Science, NumPy- Arrays, Standard Data Types, UFuncs, Aggregates, Broadcasting. Pandas- Series Object, DataFrame Object, Handling Missing Data, Trade-Offs in Missing Data Conventions, Missing Data in Pandas, Operating on Null Values, Combining Datasets: Concat and Append, Aggregation and Grouping, Matplotlib

Day 2: Linear Regression with Boston Housing Price Dataset, Logistic Regression with Titanic Dataset

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C/C++ WORKSHOP

Day 1:Brief history of C, Constants and Variables, Keywords, Data Types in C, Operators, Storage Class, Functions and Conditional statements

Day 2:Looping Statements, Introduction to Arrays and Strings in C

Day 3:Pointers in C and Transition from C to C++

Day 1 Day 2 Day3

DATA STRUCTURES WORKSHOP

Day 1:Introduction to Data Structures, Stacks, Queues, Linked Lists, Linked Stacks and Linked Queues.

Day 2:Trees, Binary Tree, Binary Tree Traversal, Binary Search Tree and Operations on BST.

Day 3:Introduction to Graphs, Terminologies, Representation of Graphs, BFS, DFS, Dijkstra's Algorithm, Weighted Graphs, Spanning Trees, Prim's and Krushkal's Algorithm

Day 1 Day 2 Day3