Learn Al from the leading
experts of Silicon Valley

An artificial intelligence course with 180 hours
of interactive classroom and video lessons

Learn Al from the leading
experts of Silicon Valley

An artificial intelligence course with 180 hours of interactive classroom and video lessons

Course Highlights

  • Designed for working IT professionals
  • Guaranteed placement assistance
  • An exclusive Tech Lounge in HITEC City
  • One-on-one mentoring by industry experts
  • In-house career counseling
  • Personalised assistance in resume building
  • 1 Capstone project, 7 assignments & 3 case studies

 

Enrol Now

Please file in your details and our team will get in touch with you

Our mentors come from

IBM
Google
Tech Mahindra
IIT Madras
oracle

Course eligibility and details

Minimum eligibility

Minimum eligibility

Basics of Statistics & Mathematics

Course fee

Course fee

₹ 1 Lakh including taxes

Learning schedule

Learning schedule

Wednesday, Saturday & Sunday

Programme location

Programme location

2nd floor, Bizness Square, Whitefields, HITEC City

Course curriculum

  • Learn about the different branches of AI, and the difference between AI, Machine Learning and Data Science.
  • Get introduced to the tools and libraries used in the worlds of data science and engineering.
  • Learn software engineering best practices that apply to AI/ML practitioners.
  • In this module, you will learn the essential foundations of Python as needed for AI programming.
  • You will learn the critical Python data types, strings, Object-Oriented Programming, data structures, and libraries (Python, NumPy, Pandas, PyTorch).
  • In this module, you will get answers to important questions such as: what is Big Data? How do we tackle Big Data? Why is the combination of AI and Big data critical?
  • You will learn You will be guided through the basics of using Hadoop with MapReduce, Spark.
  • Mathematics plays an important role as it builds the foundation for AI programming. This module will help you get you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Deep Learning.
  • The module breaks the difficult mathematical concepts into easier to understand concepts. The course covers three main mathematical theories: Linear Algebra, Multivariate Calculus and Probability Theory
  • Machine learning uses interdisciplinary techniques such as statistics, linear algebra, optimization, and computer science to create automated systems that can sift through large volumes of data at high speed to make predictions or decisions without human intervention.
  • In this module, you will learn with a broad cross-section of models and algorithms for machine learning, and prepare you for the industry application of machine learning techniques.
  • You will explore the most important supervised and unsupervised machine learning algorithms. You also will learn when and how to implement these algorithms at scale.
  • Deep Learning is one of the most highly sought-after skills in technology.
  • In this module, you will establish a thorough foundation in deep learning and build real-world applications.
  • You will learn about neural network principles and engineering frameworks such as Keras and PyTorch
  • And learn how to lead successful deep learning projects. You will learn about Convolutional networks, RNNs, LSTM
  • Learn NLP with foundations in text data, including how to clean and process it, and how to extract insights from text and conversations.
  • You will work through a detailed case study and solve a real NLP problem using deep learning and other techniques.
  • This module will introduce you to basic methods in Artificial Intelligence, including probabilistic inference, planning and search, localization, tracking and control, all with a focus on robotics.
  • Included are programming examples and assignments that will apply these methods in the context of building self-driving cars/robots moving in two dimensions.
  • Apply what you’ve learned in this course by developing a realistic, large-scale, deployed AI system.
  • Learn about common tools and techniques, deploying ML applications, real-time data processing, and making your application available via API or a web service.
  • You will build and deploy Large-Scale AI Systems. You will apply what you’ve learned in this course by developing a realistic, large-scale, deployed AI system.
  • You will learn about common tools and techniques, deploying ML applications, real-time data processing, and making your application available via API or a web service.
  • Build a realistic, complete, large-scale API application that’s available to use via an API, a web service, or — optionally — a website.
  • You’ll have free access to a cloud-based engineering environment, which will support all of the standard tools and libraries.
  • You will build and deploy Large-Scale AI Systems. You will apply what you’ve learned in this course by developing a realistic, large-scale, deployed AI system.
  • You will learn about common tools and techniques, deploying ML applications, real-time data processing, and making your application available via API or a web service.
  • Build a realistic, complete, large-scale API application that’s available to use via an API, a web service, or — optionally — a website.
  • You’ll have free access to a cloud-based engineering environment, which will support all of the standard tools and libraries.

Our network of world-class experts

Moenes Iskarous
Moenes Iskarous
PhD in Neural Networks and Robotics
Bipin Thomas
Bipin Thomas
AI Program Chair
Rahul Bhuman
Rahul Bhuman
Head- AI Business & Strategy, Tech Mahindra
Jeremiah Liou
Jeremiah Liou
Autonomous Systems Developer
Pandian Angaiyan
Pandian Angaiyan
CTO, Tech Mahindra
Sumit Gupta
Sumit Gupta
VP of Products, AI, Machine Learning, and HPC