Preamble

Intelligent machines have replaced human capabilities in many areas. Artificial intelligence is the intelligence exhibited by machines or software. It is the branch of computer science that emphasizes on creating intelligent machines that work and react like humans. Artificial Intelligence spans a wide variety of topics in computer science research, including machine learning, deep learning, reinforcement learning, natural language processing, reasoning, perception etc.

Objective of the Course

This seven-week course presents the components of Artificial Intelligence to the participants. The participants will get to work with Machine learning, Neural Networks, explore the Platforms for AI, implement methods to solve problems using Artificial Intelligence.

Outcome of the Course

This course is designed at par with the industry requirements to provide the participants in‐depth knowledge and skills required by AI field around the globe. It provides comprehensive knowledge about the fundamental principles, methodologies and industry practices in AI.

Course Contents :

Python Programming

• An Introduction to Python
• Beginning Python Basics
• Python Program Flow 
• Functions & Modules 
• Exceptions Handling 
• File Handling 
• Classes in Python 

Statistical Concepts

• Descriptive & Inferential Statistics, 
• Probability Concept: Marginal, Joint & Conditional Probability, Bayes Theorem 
• Probability Distributions
• Hypothesis Test
• Entropy & Information Gain
• Regression & Correlation
• Confusion Matrix, Bias & Variance 

Data Sience & Analytics

• An Introduction to Data Science and 
• Analytics 
• Data Analysis Using NumPy 
• Data Analysis Using Pandas 
•  Data Visualization – Pandas,Matplotlib, Seaborne, Plotly and Cufflinks

Machine Learning 

• Introduction to Machine Learning 
• Linear Regression 
• Logistic Regression 
• K-Means Clustering 
• Decision Tree 
• Random Forest 
• K-Nearest Neighbours 
• Support Vector Machine 
• Naive Bayes 
• Principal Component Analysis (PCA)

Deep Learning

• Introduction to Deep Learning
• Artificial Neural Network - ANN
• Loss Function
• Bias & Gradient Descent
• Stochastic Gradient Descent
• Convolution Neural Networks - CNN
• Recurrent Neural Networks - RNNs
• Natural Language Processing - NLP
• Computer Vision using OpenCV
• Deployment

Case Studies

• Covid-19 data Analysis
• Data Pre-processing and Data Analysis for Banking Application
• Predictive Analysis for Housing Prices
• Kaggle’s Titanic Survival
• Numerical Digit Image Classification using Regression Algorithm
• Medical Diagnosis using ML (Diabetic and Cancer)
• Implementation of Spam filtering messages for Mails
• Hand Written Number Image Classification Using CNN
• Complex image recognition (CIFAR) using DL
• Creating Sin wave Signal using RNN
• Use Deep Learning for medical imaging

Project

• Participants should do an Industry relevant project based on a data of their choice

Course Fee: Rs 12,000/-
Course Start Date: 6 Dec2022
Duration: 7 Weeks
Last Date for Registration and Payment: 25 Nov2022

 

Course Coordinator
Vimala Mathew, Scientist ‘E’/ Director in Charge

Contact Number
9316878092
Email: vimala@nielit.gov.in

Admission

Candidates can apply through online registration through this link https://forms.gle/sppJFJdkeanbubpS8, uploading payment details for Rs 1,000 (Registration Fee) while doing registration. Selected candidates will be informed through mail/ Selection list will be uploaded in website on 1st August. Students can come to the campus with the following documents to take admission

1. Proof of Eligibility
2. Passport size photograph
3. Any one Identity card. 
4. Community Certificate ( for SC/ST candidates for availing fee waiver, Aadhar Number is compulsory)
5. Course Fee as per Course Prospectus.

Mode of payment

Payment transaction may be done to the bank account using any mode of payment.

Account Name	NIELIT Daman
Account Number	40755996161
IFSC Code	SBIN0002671
Bank Name	STATE BANK OF INDIA
Branch	Moti Daman

 

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