DIPLOMA IN MACHINE LEARNING

[Note: The program comes in two formats: weekday format for fresh graduates and weekend format for working professionals.]

COURSE DESCRIPTION (Course Type - Diploma)

COURSE LEARNING

Upon completion of this course, you will be able to:

MODULE 1 - PYTHON PROGRAMMING

Introduction to programming and Python Data types | Operators |Expressions | Conditionals | Loops | Functions | Recursion | OOPS Concepts Data Structures | Numpy | Pandas | Error Handling | Scikit-learn library

MODULE 2 – Data Analysis

Introduction to EDA | Deal with missing data |Data Cleaning | Data visualization

MODULE 3 - MACHINE LEARNING

Introduction to Supervised Learning and Unsupervised Learning | Linear Regression | Logistic Regression | | Decision Trees and Random Forest | Support Vector Machines (SVM) | K-Means Clustering | Hierarchical Agglomerative Clustering

MODULE 4 - DEEP LEARNING

Introduction to Deep Neural Network

Course Project

·         Hand written digits CLASSIFICATION

·         HOUSE PRICE PREDICTION

Course Duration and Learning pattern

Duration of Certificate – 3 Week

Classes’ distribution – 50% Theory Classes and 50% Implementation

Key Highlights

Assignments Students will receive timely assignment related with course topics.

          Attendance Policy 85%

          Instructor Feedback One can directly report about the feedback of instructor.