Guest lectures

Objective:
  1. Understand the Big Data Platform and its Use cases
  2. Provide an overview of Apache Hadoop
  3. Provide HDFS Concepts and Interfacing with HDFS
  4. Understand Map Reduce Jobs
  5. Apply analytics on Structured, Unstructured Data.
  6. Exposure to Data Analytics with R.

Introduction to AI; Advanced search techniques in AI: Heuristic search, Local search, Adversarial search; Genetic and evolutionary algorithm, Knowledge-based system design: Propositional logic,  First-order logic, Planning logic, Modeling constraint satisfaction and optimization problems in MiniZinc; Advanced plan generating systems: Automated classical planning, Partial-order planning (POP), SAT Planning, Hierarchical task network (HTN) planning; Bayesian network and probabilistic reasoning: Uncertain reasoning, Probabilistic reasoning, Bayesian Network, Dynamic Bayesian Network; Introduction to deep learning: Deep belief network, Deep neural network, deep learning for natural language processing and computer vision; Introduction to Robotics and Robot programming.