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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Post Graduate Program in Artificial Intelligence & Machine Learning is a comprehensive and hands-on course. The course is 12 months and is provided in a fully online mode. It covers cutting-edge technologies like Deep Learning, Computer Vision, NLP, and Reinforcement Learning, along with practical projects and industry insights.

The Post Graduate Program in Artificial Intelligence and Machine Learning certification by Great Learning and the University of Texas at Austin is designed by expert faculty to ensure a great learning experience. Through this programme, learners gain valuable skills and knowledge to excel in AI and ML roles.

In the Post Graduate Program in Artificial Intelligence and Machine Learning training, candidates will receive career support, resume reviews, and interview preparation. You will also get access to a vast job board with opportunities from 2800+ companies. Whether you are a beginner or an experienced professional, this programme can open doors to promising career prospects in the dynamic field of Artificial Intelligence and Machine Learning.

Also Read: Artificial Intelligence And Machine Learning Certification Courses

The Highlights

Hands-On Experience
Case Studies
Offered by the University of Texas at Austin
12 Months Duration
Online Bootcamp
Flexible Learning

Programme Offerings

Mentorship Session
assignments
Readings
LIVE Webinar
discussion forum
Capstone Project
Experiential Learning

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Great LearningTexas McCombs

The Post Graduate Program in Artificial Intelligence and Machine Learning certification fees can be paid through net banking, or credit/debit card. You can also apply for an educational loan at 0% interest.

Post Graduate Program in Artificial Intelligence and Machine Learning Fee

Mode of Enrolment	Fee
Total Fee	Rs.2,75,000+GST

Eligibility Criteria

Educational Qualification

A bachelor’s degree in any discipline with a minimum of 50% marks is required.

What you will learn

Machine learningKnowledge of PythonKnowledge of Artificial IntelligenceKnowledge of deep learning

By the end of the Post Graduate Program in Artificial Intelligence and Machine Learning certification syllabus, candidates will be able to have a comprehensive understanding of AI and ML concepts, algorithms, and technologies. He/She will also learn concepts of Deep Learning, Computer Vision, NLP, and Reinforcement Learning. Candidates will become job-ready with resume preparation, interview skills, and access to job opportunities from top companies. Candidates will get hands-on experience in implementing AI and ML projects, working with real-world datasets, and using popular tools and frameworks like TensorFlow, Keras, and OpenCV.

Who it is for

Software DeveloperData ScientistSoftware EngineerIT EngineerAI Data Analyst

Post Graduate Program in Artificial Intelligence and Machine Learning classes are designed for individuals who are in the following fields:

Admission Details

Enrol in the Post Graduate Program in Artificial Intelligence and Machine Learning online course by following these simple steps:

Step 1: Access the course via: https://www.mygreatlearning.com/pg-program-artificial-intelligence-course.

Step 2: Click on the “Apply Now” button.

Step 3: Fill up an application form.

Step 4: Submit the application and start by attending the demo class.

Step 5: You will receive an interview call for further processing.

Step 6: An offer letter will be provided to the selected candidate.

Application Details

In this application form, the applicant needs to provide their basic information, including their name, mobile number, and email address. They need to specify their work experience and any programming experience. The applicant needs to agree to the Terms and Conditions and the Privacy Policy before proceeding.

After that, they need to share their education details for their undergraduate programme. The applicant is required to select their degree type from the available options and provide information about their college/university name, year of graduation, and their CGPA or percentage. These details are necessary to determine if they meet the eligibility criteria, which require a minimum of 50% in any undergraduate programme. Once completed, the applicant can submit the form.

The Syllabus

Module 1 - Introduction to Python

Python Basics

Python Functions and Packages
Working with Data Structures, Arrays, Vectors & Data Frames
Jupyter Notebook – Installation & Function
Pandas, NumPy, Matplotlib, Seaborn

Self Paced Module - EDA and Data Processing

Data Types
Dispersion & Skewness
Uni & Multivariate Analysis
Data Imputation
Identifying and Normalizing Outliers

Module 2 - Applied Statistics

Descriptive Statistics
Probability & Conditional Probability
Hypothesis Testing
Inferential Statistics Probability Distributions

Module 1 - Supervised learning

Linear Regression
Multiple Variable Linear Regression
Logistic Regression
Naive Bayes Classifiers
k-NN Classification
Support Vector Machines

Module 2 - Ensemble Techniques

Decision Trees
Bagging
Random Forests
Boosting

Module 3 - Unsupervised learning

K-means Clustering
Hierarchical Clustering
Dimension Reduction-PCA

Module 4 - Featurisation, Model Selection & Tuning

Feature engineering
Model selection and tuning
Model performance measures
Regularising Linear models
ML pipeline
Bootstrap sampling
Grid search CV
Randomized search CV
K fold cross-validation

Module 5 - Recommendation Systems

Introduction to Recommendation Systems
Popularity based model
Content based Recommendation System
Collaborative Filtering (User similarity & Item similarity)
Hybrid Models

Module 1 - Introduction to Neural Networks and Deep Learning

Introduction to Perceptron &
Neural Networks
Activation and Loss functions
Gradient Descent
Batch Normalization
TensorFlow & Keras for Neural Networks
Hyper Parameter Tuning

Module 2 - Computer Vision

Introduction to Convolutional Neural Networks
Introduction to Images
Convolution, Pooling, Padding & its Mechanisms
Forward Propagation & Backpropagation for CNNs
CNN architectures like AlexNet, VGGNet, InceptionNet & ResNet
Transfer Learning
Object Detection
YOLO, R-CNN, SSD
Semantic Segmentation
U-Net
Face Recognition using Siamese Networks
Instance Segmentation

Module 3 - NLP (Natural Language Processing)

Introduction to NLP •
Stop Words •
Tokenization •
Stemming and Lemmatization
Bag of Words Model
Word Vectorizer
TF-IDF
POS Tagging
Named Entity Recognition
Introduction to Sequential data
RNNs and its Mechanisms
Vanishing & Exploding gradients in RNNs
LSTMs - Long short-term memory
GRUs - Gated Recurrent Unit
LSTMs Applications
Time Series Analysis
LSTMs with Attention Mechanism
Neural Machine Translation
Advanced Language Models: Transformers, BERT, XLNet

Self Paced Module - Introduction to Reinforcement Learning (RL)

RL Framework
Component of RL Framework
Examples of RL Systems
Types of RL Systems
Q-learning

Self Paced Module - Introduction to GANs (Generative Adversarial Networks)

Introduction to GANs
Generative Networks
Adversarial Networks
How do GANs work?
DCGANs - Deep Convolution GANs
Applications of GANs

Additional Module

Power BI
Cloud Computing
Block Chain

Instructors

Texas McCombs Frequently Asked Questions (FAQ's)

1: Are there any real-world projects included in the Post Graduate Program in Artificial Intelligence and Machine Learning online programme?

Yes, the programme includes 12+ hands-on projects that provide practical experience in implementing AI/ML solutions.

2: Does the programme offer career support?

Yes, the programme provides career support with resume review, interview preparation, and access to a job board with job opportunities from 2800+ companies.

3: Will I receive a certificate upon completion of the programme?

Yes, participants who successfully complete the programme will receive a certificate from the institute.

4: Can I apply for financial aid or education loans?

Yes, the programme offers financial aid and collaborations with financial partners for education loans at a 0% interest rate to eligible candidates.

5: How do I apply for the Post Graduate Program in Artificial Intelligence and Machine Learning online programme?

Interested candidates can apply by filling out the online application form and providing the required information, including personal, educational, and professional details.