DRDO is offering a 12 weeks online course on Artificial Intelligence & Machine Learning 120 contact hours [2 hours/day & 5 days/week].
The training and certification course is a 12 weeks online course offering a mix between fundamentals and advanced topics of AI & ML such as Probability Theory, Pattern Recognition, Big Data Analytics, Computer Vision, Natural Language Processing, Augmented Reality, Deep Learning, and related advancements in the domain. The syllabus is designed by leading academicians and AI experts from DRDO.
The training sessions are offered by leading academicians, experts from DRDO, and national and international AI professionals from industry and AI think tanks.
Course Framework
- Module-1: Probability Theory and Pattern Recognition
- Module-2: Machine Learning & Deep Learning
- Module-3: Computer Vision
- Module-4: Big Data Analysis and Algorithms
- Module-5: Natural Language Processing
- Module-6: Augmented Reality
Eligibility: Graduates from any discipline aiming for a successful career in Artificial Intelligence and Machine Learning. IT professionals who wish to enhance their AI skills, Officers from Tri-services, R&D professionals, or anyone who wants to develop expertise in the field of AI. Students pursuing graduation may apply.
Machine Learning & Deep Learning
Introduction to AI, ML & Deep learning, Methods and Concepts for AI & ML, Artificial Neural Networks: Basics of Neuron, Perceptron, Multilayer Neural Network, Back-propagation Algorithm; Introduction to Deep Neural Networks, Convolutional Neural Networks, Image Classification using CNN, Recurrent Neural Networks & Auto-encoders, and Generative Adversarial Networks (GANs).
Syllabus Details
Basic probability and measures of dispersion, Random Variable, Probability function, and Joint probability function Binomial and Poisson distribution, Normal distribution, Application to learning using Bayesian method, Introduction to Pattern Recognition Systems, Classification, Types of Classification, Linear and Non-Linear Classification, Dimensionality Reduction & Feature Selection Methods: Linear Discriminant Analysis and Principal Component Analysis, Introduction to Clustering, Algorithms: Distance Based Clustering: Distance-based and Density-based, Predictive Modelling, Case Studies.
Important Dates
- Last date of Registration: 25 May 2023
- Last date of payment of fees: 05 June 2023
- Commencement of Course: 12 June 2023
To register for the course: CLICK HERE
