Courses

Python || Machine learning || Java || Algorithms


  • Python

    Syllabus Download

    • Program in Python
    • Operators and Expressions
    • Loops and Iteration
    • Conditional Code, Functions
    • Lists and Importing Libraries
    • Tuples, Data Dictionaries
    • Modules, Python Packages
    • Error and Exceptions
    • Object Oriented Programming
    • Inheritance
    • Applied Python

  • Machine learning

    Syllabus Download

    • Machine learning concepts
    • Supervised learning methods
    • Classification and Regression
    • Using the scikit-learn library
    • Core components of TensorFlow
    • Support vector machines
    • Machine learning model training
    • Advanced supervised learning
    • Neural networks
    • Deep learning

  • Java

    Syllabus Download

    • Object Oriented Programming
    • Arrays, Lists, and Structured Data
    • Data Structures and Performance
    • Advanced DS in Java
    • Generics and Functions
    • STL and the game of Hex
    • Advanced Java Topics
    • Reflection Native Interface
    • String and Patterns
    • Graph and Inheritance
    • Java Multithreading
    • Java Network Programming
    • Enterprise Java

  • Algorithms

    Syllabus Download

    • Data Structures
    • Algorithmic Analysis
    • Heaps and the Disjoint Sets
    • Recursion: Divide and Conquer
    • Dynamic Programming
    • Greedy, Graph Traversal
    • Computational Complexity
    • Distributed Algorithms
    • Robot Algorithms
    • Scheduling Algorithms
    • Parallel Algorithms
    • AI Search Algorithms
    • Network Algorithmics

  • Data Structures

    Syllabus Download

    • Prgramming Overview
    • Recursion
    • Pointers and Array-Based Lists
    • Linear Lists, Stack, Queues
    • Non-Linear Lists
    • Trees, Graphs
    • BST, AVL, RB, etc.
    • Heaps, Multiway Trees
    • Sorting and Searching

  • Data Science

    Syllabus Download

    • The Data Scientist’s Toolbox
    • Python | R
    • Getting and Cleaning Data
    • Exploratory Data Analysis
    • Reproducible Research
    • Statistical Inference
    • Regression Models
    • Practical Machine Learning
    • Developing Data Products
    • Data Science Capstone

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