220 Hours of Artificial Intelligence & Machine Learning

Features

Lectures - 20
Duration - 12 Weeks
Case Studies and Assessment - 10+
Delivery Mode - Online/Offline
Batches - Weekdays/Weekend
Capstone Projects - 15 projects( Choose anyone)

Overview
Curriculum
Instructor
FAQs

Artificial Intelligence is the need of the Future. We will have to get prepared for the future from today. Artificial Intelligence helps us in solving difficult problems with an ease with very less human intervention.

Program Overview

This Program is specially designed to give a strong foundation to become a ML & AI Specialist. You will get a brief knowledge on Machine Learning, Deep Learning and Artificial Intelligence. After completing this course, you will be able to solve business problems using Data Science & AI.

Program Structure

Pre-Learning: Before you come in, get ready for the program. You will get a series of online tutorials on basic Statistics, Python, Deep Learning and Machine Learning.
60 Hours Program: Here, you will get hands-on experience in Python Programming, Machine Learning, Deep Learning, NLP, Computer Vision and Reinforcement Learning.
Post Program:Learning does not stop here. After completing the program, you will work on capstone project, case studies. Doubt clearing session is provided post program. You will be working on any 1 capstone project from the list of few projects on your choice.

Eligibility:

Education – Graduate in Math, Science, Commerce, Statistics, Economics or Management.
Work Exp –Fresher or Experienced in any disciplinary field. Basic knowledge of Python and Machine Learning is Must.

Sample Certificate

Python Programming [5 hours]
Introduction to python, Variables, Operators, Datatypes and its operations, Data structures and its operations, Functions, **kwargs, *args, Module, Class, Numpy, Pandas, Matplotlib, Seaborn
- .
Machine Learning [10 hours]
Introduction to Machine Learning, Types of Machine Learning, Linear regression, Logistics Regression, Support Vector Machine, K Nearest Neighbour, Naïve Bayes, Decision Tree, Random Forest, PCA,
- .
Computer Vision [10 Hours]
Introduction to Image Processing, Feature Detection, OpenCV, Convolution, Padding, Pooling & its Mechanisms, Forward Propagation & Backward Propagation for CNN, CNN Architectures , AlexNet, VGGNet, InseptionNet, ResNet, Transfer Learning
- .
Basic of NLP (Natural Language Processing) [7 Hours]
Introduction to text mining, text processing using python, Introduction to NLTK, Tokenization, Stemming, Bag of words Sentiment Analysis, Name- Entity Recognition, Text Segmentation, Text Mining, Text Classification
- .
Deep Learning [12 hours]
Introduction to Deep Learning, Feed Forward Network, Fully Connected Network, Activation Functions, Optimizers
- .
Introduction to Reinforcement Learning [8 Hours]
RL Framework, Component of RL Framework, Examples of Systems, Types of RL Systems, Q-Learning
- .
Live Project and Doubt Clearing [8 Hours]
- .
Program Benefits
Skills you will possess post program
Capstone Projects.

emergingindiagroup

What is this program all about?

This is an Advanced Data Science Program which will help candidates to make their career in Artificial Intelligence.

Is there any loan facility / sponsorships available?

Yes, we have tie-up with one of the renowned financial institutions, so we can help you in getting education loans with 0% rate of interest. The approval is based on the income and occupation. EMI options are available based on Credit Cards upto 12 to 18 installments. Yes, we also guide candidates in getting sponsorships from their companies.

What is the system configuration required for the training?

Own Laptop with configuration: At least 4 GB Ram, above or similar i3 processor.

Will I get recorded videos and study material during and after completion of the course?

Yes, after each lecture, recorded videos of that lecture will be available to the LMS of each candidate which you can download. All the material that is required during the course will be provided to the candidates.

What is the refund policy?

Please refer to the link for Terms and Conditions

220 Hours of Artificial Intelligence & Machine Learning

Features

Program Overview

Program Structure

Eligibility:

Sample Certificate

Python Programming [5 hours]
Introduction to python, Variables, Operators, Datatypes and its operations, Data structures and its operations, Functions, **kwargs, *args, Module, Class, Numpy, Pandas, Matplotlib, Seaborn

Machine Learning [10 hours]
Introduction to Machine Learning, Types of Machine Learning, Linear regression, Logistics Regression, Support Vector Machine, K Nearest Neighbour, Naïve Bayes, Decision Tree, Random Forest, PCA,

Computer Vision [10 Hours]
Introduction to Image Processing, Feature Detection, OpenCV, Convolution, Padding, Pooling & its Mechanisms, Forward Propagation & Backward Propagation for CNN, CNN Architectures , AlexNet, VGGNet, InseptionNet, ResNet, Transfer Learning

Basic of NLP (Natural Language Processing) [7 Hours]
Introduction to text mining, text processing using python, Introduction to NLTK, Tokenization, Stemming, Bag of words Sentiment Analysis, Name- Entity Recognition, Text Segmentation, Text Mining, Text Classification

Deep Learning [12 hours]
Introduction to Deep Learning, Feed Forward Network, Fully Connected Network, Activation Functions, Optimizers

Introduction to Reinforcement Learning [8 Hours]
RL Framework, Component of RL Framework, Examples of Systems, Types of RL Systems, Q-Learning

Live Project and Doubt Clearing [8 Hours]

Program Benefits

Skills you will possess post program

Capstone Projects.

emergingindiagroup

How to Train a GPT Model: A Step-by-Step Guide

AutoGen: A Step-by-Step Implementation Guide

Python vs Julia: Which Programming Language Should You Choose in 2024?

220 Hours of Artificial Intelligence & Machine Learning

Features

Program Overview

Program Structure

Eligibility:

Sample Certificate

Python Programming [5 hours] Introduction to python, Variables, Operators, Datatypes and its operations, Data structures and its operations, Functions, **kwargs, *args, Module, Class, Numpy, Pandas, Matplotlib, Seaborn

Machine Learning [10 hours] Introduction to Machine Learning, Types of Machine Learning, Linear regression, Logistics Regression, Support Vector Machine, K Nearest Neighbour, Naïve Bayes, Decision Tree, Random Forest, PCA,

Computer Vision [10 Hours] Introduction to Image Processing, Feature Detection, OpenCV, Convolution, Padding, Pooling & its Mechanisms, Forward Propagation & Backward Propagation for CNN, CNN Architectures , AlexNet, VGGNet, InseptionNet, ResNet, Transfer Learning

Basic of NLP (Natural Language Processing) [7 Hours] Introduction to text mining, text processing using python, Introduction to NLTK, Tokenization, Stemming, Bag of words Sentiment Analysis, Name- Entity Recognition, Text Segmentation, Text Mining, Text Classification

Deep Learning [12 hours] Introduction to Deep Learning, Feed Forward Network, Fully Connected Network, Activation Functions, Optimizers

Introduction to Reinforcement Learning [8 Hours] RL Framework, Component of RL Framework, Examples of Systems, Types of RL Systems, Q-Learning

Live Project and Doubt Clearing [8 Hours]

Program Benefits

Skills you will possess post program

Capstone Projects.

emergingindiagroup

Zero Cost EMI options Available From RBI Approved NBFCs

How to Train a GPT Model: A Step-by-Step Guide

AutoGen: A Step-by-Step Implementation Guide

Python vs Julia: Which Programming Language Should You Choose in 2024?

Modal title

Python Programming [5 hours]
Introduction to python, Variables, Operators, Datatypes and its operations, Data structures and its operations, Functions, **kwargs, *args, Module, Class, Numpy, Pandas, Matplotlib, Seaborn

Machine Learning [10 hours]
Introduction to Machine Learning, Types of Machine Learning, Linear regression, Logistics Regression, Support Vector Machine, K Nearest Neighbour, Naïve Bayes, Decision Tree, Random Forest, PCA,

Computer Vision [10 Hours]
Introduction to Image Processing, Feature Detection, OpenCV, Convolution, Padding, Pooling & its Mechanisms, Forward Propagation & Backward Propagation for CNN, CNN Architectures , AlexNet, VGGNet, InseptionNet, ResNet, Transfer Learning

Basic of NLP (Natural Language Processing) [7 Hours]
Introduction to text mining, text processing using python, Introduction to NLTK, Tokenization, Stemming, Bag of words Sentiment Analysis, Name- Entity Recognition, Text Segmentation, Text Mining, Text Classification

Deep Learning [12 hours]
Introduction to Deep Learning, Feed Forward Network, Fully Connected Network, Activation Functions, Optimizers

Introduction to Reinforcement Learning [8 Hours]
RL Framework, Component of RL Framework, Examples of Systems, Types of RL Systems, Q-Learning