Artificial Intelligence and Robotics
About the course
BICARD combines Practical learning to Industrial Efficiency. This Artificial Intelligence and Robotics course can lead to a career such as a designer of intelligent systems or in research. The core modules are: Artificial Intelligence (AI) with robotics, neural computation and machine learning, Practicals and Theory related to Artificial Intelligence.
Students will work in the Industry based on the knowledge of :
- Design and develop advanced knowledge-based and multi-agent software systems
- Design and develop robotic systems for services and industrial applications, including safety and security, space, home, care of the elderly, medicine
- Design and develop computer animation systems for the movie and videogame industries
- Design and develop video systems for environmental, production and service surveillance and monitoring
- Compose and coordinate research and development teams in advanced technology companies
- Plan, supervise, design and implement, when possible through interdisciplinary teams, innovative applications in information technology and related areas such as automation, telecommunications, and resource management
- Promote the technological transfer of research results and technological advancements to public and private organizations
- Manage and train human resources for information technology.
Career opportunities :
Embedded Systems is among the fastest-growing fields with unlimited opportunity in nearly every industry. Artificial Intelligence and Robotics course provides the knowledge and tools to the design and implementation of information processing systems and their specific components.
Engineers with the Artificial Intelligence and Robotics Post graduate diploma qualify for jobs in information technology, with focus on Artificial Intelligence, Robotics, or Computer Graphics.
Typical examples of target activities are:
- automation and robotics
- software development
- dedicated and embedded systems design
Potential job titles include:
- Knowledge engineer
- Robotics engineer
- Computer graphics engineer
- Project manager
- Applications engineer
- Design engineer
- Development engineer
Out-line of course contents
|What is intelligence?||Neural networks|
|Expert Systems||Applications of AI: Games-playing|
|Artificial Intelligence||AI-Applications of AI: Artificial examiners (exam grading)|
|Heuristics||Civilian applications for drones|
|Computational Intelligence||Industrial robots|
|Pattern recognition||Ethical issues|
|Natural language processing||Robotic input devices|
|Representing knowledge||Robotic output devices|
Subjects of study during this course
- Computer Organization & Architecture
- Mathematical Foundations of Computer Science
- Data Structures & Algorithms
- Operating Systems – Overview
- Programming Lab
- Fundamentals of Robotics
- Principles of Robotics
- Robotics Lab
- Embedded systems
- Machine Learning
- Supervised and Unsupervised Learning
- Supervised Learning
- Regression: Linear, Logistic
- Neural Networks
- Fuzzy Systems (overview)
- Support Vector Machines (SVMs)
- Unsupervised Learning
- Anomaly Detection
- Recommender Systems
- Artificial Intelligence
- Expert Systems
- Concepts and Application Areas
- Pattern Recognition
- Natural Language Processing
- Image Processing
- Computer Vision
- AI & Expert Systems Lab
Bachelor’s Degree in Engineering (Computer Science / Electronics / IT / IT & Telecommunications / Electrical / Instrumentation and other allied streams). 60 % marks as aggregate in qualifying examination.
PG Degree in relevant stream (e.g. MSc in Mathematics, Statistics, Computer Science, IT, Electronics). 60% marks as aggregate in qualifying examination.
Also Equally Required:
- Strong liking for Mathematics, Logical Reasoning
- Analytical Bent of Mind
- Desire to Learn
- Willing to put sincere efforts and time to pick up new concepts
No of Seats:
Artificial Intelligence and Robotics
- The online entrance test for AI& Robotics) will be conducted at notified Venue on the date & time as mentioned in the schedule table.
- Questions will be of objective nature, with each question having four Alternative answers.
- There will be negative marking of 25% of the marks allotted to the Question for wrong answer.
- The aspects to be covered will be Quantitative Ability; Analytical and Logical Reasoning; Language Ability;
- Linear Algebra: Matrix algebra, Systems of linear equations, Eigen values and eigenvectors. Calculus: Functions of single variable, Limit, continuity and differentiability, Mean value theorems, Partial derivatives, Total derivative, Maxima and minima, , Differential Equations: First order equations (linear and nonlinear), Higher order linear differential equations with constant coefficients.
- Probability and Statistics: Definitions of probability and sampling theorems, Mean, median, mode and standard deviation, Random variables, Poisson, Normal and Binomial distributions.
- Programming in C; Functions, Recursion, Parameter passing, Scope, Binding; Abstract data types, Arrays, Stacks, Queues, Linked Lists, Trees, Binary search trees, Binary heaps. Algorithms: Analysis, Asymptotic notation, Notions of space and time complexity, Worst and Average case analysis;
- Operating System: Processes, Threads, Inter-process communication, Concurrency, Synchronization, Deadlock, CPU scheduling, Memory management and virtual memory, File systems, I/O systems, Protection and security.
- Databases: ER-model, Relational model (relational algebra, tuple calculus), Database design (integrity constraints, normal forms), Query languages (SQL), File structures (sequential files, indexing, B and B+ trees), Transactions and concurrency control. Information Systems
- The aspects to be covered will be Quantitative Ability; Analytical and Logical Reasoning; Language Ability; Mathematics / Business; Mathematics / Statistics up