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The University of Texas at Austin | Post Graduate Program in Artificial Intelligence and Machine Learning

Earn internationally recognized dual certificates from The University of Texas at Austin and Great Lakes Executive Learning.

Course Snapshot
  • Fee2,40,000 + GST
  • Work Experience2 - 30 Years
  • Duration12 Months - 255+ hours of learning
  • Delivery MethodOnline
Course Detail

Program Overview
The Program in AI & Machine Learning from University of Texas at Austin & Great Lakes covers Artificial Intelligence & Machine Learning technologies and applications including Machine Learning, Deep Learning, Computer Vision, Natural Language Processing, Reinforcement Learning, Neural Network, Tensor Flow and many more. Hands-on program using AI and ML lab and 12+ projects. It features case studies and learning from some of the top global companies like Uber, 2 Netflix, Google, Amazon etc. For every assignment you work as part of this program, you will get to see the solutions of the assignment as recorded walkthroughs. Recorded walkthroughs help you to understand the concepts better and analyze a problem from the view of an expert. As part of this program, you will be making all of your submissions on Github. Github is an online repository which helps you to store all the projects and assignments you have done as part of this program in a single place. Today, most companies look at potential recruits Github profiles to check their technical expertise before hiring them

About The University of Texas at Austin
The University of Texas at Austin is one of the largest schools in USA. It was founded in 1883. Today UT Austin is a world-renowned higher education, research-intensive institution, serving more than 51,000 students annually with a teaching faculty of around 3,000. University of Texas at Austin is ranked #4 worldwide for Business Analytics according to the QS University rankings 2020.

Program Highlights
● Earn internationally recognized dual certificates from The University of Texas at Austin and Great Lakes Executive Learning.
● Hands-on program using AI and ML lab and 5+ projects. It features case studies and learning from some of the top global companies like Uber, 2 Netflix, Google, Amazon etc.
● Develop expertise in popular AI & ML technologies and problem-solving methodologies
● Develop the ability to independently solve business problems using AI & ML
● Develop a verified portfolio with 12+ projects that will showcase the new skills acquired
● Build expertise in AI & ML which are quickly becoming the most sought-after skills around the world
● Learn to use popular AI & ML technologies like Python, Tensorflow and Keras to develop applications

Industry Projects
Learn through real life industry projects such as:
● To identify the potential customers who have a higher probability to churn using ensemble prediction model
● To cluster the vehicles as per their fuel consumption attributes and later train a regression model for an automobile dataset
● To create an automation using computer vision to impute dynamic bounding boxes to locate cars or vehicles on the road.
● Implementing an Image classification neural network to classify Street House View Numbers
● Predicting the condition of the patient depending on the received test results
● To build a NLP classifier which can use input text parameters to determine the label/s of the blog.
● To build a recommendation system using popularity based and collaborative filtering methods to recommend mobile phones to a user which are most popular and personalized respectively.
● Sarcasm Detection using Bidirectional LSTMs
● To build a semi-rule based text chat bot which can give static responses to the user depending on the inputs for industrial safety and incidents
● To build an image classifier and object detection model which can classify a car from an image and identify the location of the car from an image by publishing a bounding box around it

Desired Candidate Profile

Applicants should have a Bachelor's degree with a minimum of 50% aggregate marks or equivalent and familiarity with programming. For candidates who do not know Python, we offer a free pre-program tutorial.

Course Modules

Foundations
● Introduction to Python
● Applied Statistics
● EDA and Data Processing

Machine Learning
● Supervised learning
● Ensemble Techniques
● Unsupervised learning
● Featurisation, Model Selection & Tuning
● Recommendation Systems
● Time-series Forecasting
● Model deployment

Artificial Intelligence
● Introduction to Neural Networks and Deep Learning
● Computer Vision
● NLP (Natural Language Processing)
● Introduction to Reinforcement Learning (RL)
● Introduction to GANs (Generative adversarial networks)