Certification Programme on
Artificial Intelligence and Deep Learning
14 - 25 June 2021 (Monday – Friday): 3 PM – 6 PM
Introduction to Artificial Intelligence and Deep Learning
- Overview and Applications of AI.
- Building AI Solutions using Deep Learning.
- Deep Learning – Neural Network using Python & R.
- Introduction to Python Libraries – Tensorflow, Keras, OpenCV.
- Perception Algorithm and Back propagation Algorithm.
- Artificial Neural Network (ANN) or Multilayer Perceptron.
Data Mining Supervised Learning/Machine Learning
- Convolution Neural Network (CNN).
- Image Processing and Computer Vision.
- Recurrent Neural Network (RNN).
- Long Short-term Memory (LSTM).
Data Mining Unsupervised Learning
- Gated Recurrent Network (GRU).
- Auto Encoder, Restricted Boltzmann Machine (RBM).
- Deep Belief Networks (DBN).
- Generative Adversarial Networks (GANs).
- Reinforcement Learning and Q-Learning.
Key Benefits/Learning Outcomes
- Understand about the Gated Recurrent Networks (GRU).
- Learn on how to build AI systems using Deep Learning Algorithms.
- Be able to deal with unstructured data such as images, videos, text etc.
- Be able to implement Deep Learning Solutions and image processing applications using convolutional networks.
- Be introduced to analyze sequence data and perform Text analytics and Natural Language Processing (NLP) using recurrent networks.
- Be able to effectively use various Python libraries such as Keras, Tensorflow, OpenCV, etc. which are used in solving AI and Deep Learning problems.
All those participants who have:
- Basic idea about programming.
- Basic mathematical knowledge should be good to start with the program.
- Candidates aspiring to become Data Scientists or Deep Learning & AI experts.
- Analytics Managers / Professionals, Business Analyst, Developer.
- People who are looking to build a career in Machine Learning, Deep Learning and AI.
- Employees of organizations, who are planning to focus on building AI applications.
- Students can also take up this program to guide their career towards the space of AI.