Certificate Program in AI/ML

What does this course cover?
The course has seven modules, including a curated list of capstone projects. The details:

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Module 1: Foundation (2 weekends - 12 hrs)

1.1 Introduction to Data Science

1.2 Fundamentals of statistics

1.3 Python Programming

• Installation

• Input and Output

• Variables

• Type Conversions

• Basic Math Operations

• Basic Boolean Operations

• String Operations

• Control Flows

• Iterables (List, Tuple, Dictionary, Set)

• Numpy

• Matplotlib

• Pandas

• Dataframes
   

1.4 Exploratory Data Analysis

• Outlier Detection

• Label encoding

• Standardization

• Normalization Module
   

Module 2: Machine Learning (3 weekends – 18 hrs)

2.1 Supervised Learning

• Linear Regression

• Logistic Regression

• Naive Based Algorithm

• Ensemble Techniques and Decision Trees

• Support Vector Machines
   

2.2 Un-Supervised Learning

• Clustering Techniques

• Principal Component Analysis (PCA)

• Model Performance and Hyper Parameter Tuning
   

Hackathon 1 (1 weekend – 6 hrs)
Module 3: Workshop on Data Visualization (16 hours)

• Microsoft Power BI

• Tableau Module

Module 4: Deep Learning (6 hrs)

• Introduction to Convolution Neural Networks

• Pre-Trained Models

• Transfer Learning

Module 5: Computer Vision (2 weekends – 12 hrs)

• Semantic Segmentation

• Image Classification

• Object Detection

• Face Detection and Face Recognition

Hackathon 2 (1 weekend – 6 hrs)
Module 6: Natural Language Processing (NLP) (2 weekends – 12 hrs)

• Text Extraction

• Convert unstructured text into structured text

• Text Classification

• Topic Modelling

• Entity Resolution

Module 7: Generative AI Foundation( 1 weekend – 6 hrs)

• Transformers Architecture

• Introduction Language Models

• Introduction to Large Language Models

Hackathon 3 (1 weekend – 6 hrs)

Capstone Project

• 1. A Curated List of projects will be provided