GPMS Transportal Applied AI For Lab Courses

1. AI For Computer Vision

Computer Vision Fundamentals

1. Computer Vision Fundamentals

Understanding the field, the process, and mechanism of working of how the computer sees the world around

Level - Basic - Mandatory - Introduction

Prerequisites - None, No Coding knowledge necessary, will be built along with the course.

Duration - 36 Hours (6 Hours per week - 2 Hrs x 3)

Assessments - Micro Assessment weekly, Full Assessment last week.

COMBINED LEARNING OUTCOME ACHIEVED

Students will be able to have an overview of the working of AI in the area of Computer Vision along with the ability to plan, assess, and create Computer Vision Strategies within companies supporting the overall life cycle of creation.

Computer Vision Fundamentals

2. DATA MANAGEMENT AND PREPARATION

A key aspect of achieving a working AI is efficient Data, prepared well to achieve the outcome that is planned.
Level- Basic - Choice - Specialisation
Prerequisites - Introduction to Computer Vision or any introduction course.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments- Micro Assessment weekly, Full Assessment last week.

COMBINED LEARNING OUTCOME ACHIEVED

Students will be able to have an overview importance of Data, preparation strategies and handle the entire data lifecycle for an organisation.

Computer Vision Fundamentals

3. DEEP DIVE INTO ALGORITHMS AND TRAINING FOR COMPUTER VISION

Understanding the nature, diversity, and process of working of algorithms that are used to train various intelligences from a Computer Vision Lens.
Level- Intermediate - Choice - Specialization
Prerequisites - Introduction to Computer Vision or any introduction course.
Duration- 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments- Micro Assessment weekly, Full Assessment last week. Midterm, and Completion.

COMBINED LEARNING OUTCOME ACHIEVED

Students will be able to have deep knowledge of algorithms, training process, and overall methodology of how the intelligence is created. Understanding drawbacks and potential pitfalls that arise in training, and how they can be fixed.

Computer Vision Fundamentals

4. QUALITY ASSURANCE AND ASSESSMENT

Assuring Quality, accuracy, model resilience, and more characteristics in cases of AI business solution development, and guaranteeing performance, and outcomes. Computer Vision Use Cases

Level - Basic - Choice - Specialisation

Prerequisites - Introduction to Computer Vision or any introduction course.

Duration - 36 Hours (6 Hours per week - 2 Hrs x 3)

Assessments - Micro Assessment weekly, Full Assessment last week.

COMBINED LEARNING OUTCOME ACHIEVED

Students will be able to have a complete understanding of the testing process of Artificial intelligence solutions, common flaws, possible solutions, and the ability to reduce time to live through effective planning and development.

Computer Vision Fundamentals

5. COMPUTER VISION USE CASES, AND END TO END LIFE CYCLE MANAGEMENT

Here students work hands on in development of Computer Vision Solutions as selected by team - 5 Solutions in 5 Weeks, and 6th week for longer term project.
Level-Intermediate - Choice - Specialisation (For Custom Solutions through industry partnerships)
Prerequisites - Introduction to Computer Vision.
Duration - 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Micro Assessment weekly, Full Assessment last week.

COMBINED LEARNING OUTCOME ACHIEVED

Students will be able to have a deep and relevant understanding of the working of AI in the area of Computer Vision along with the ability to plan, assess, and create Computer Vision Strategies within companies supporting the overall life cycle of creation.

Computer Vision Fundamentals

6. STARTUP, PROJECT, INNOVATION

Working on custom problems of industry, or your own startup/innovative projects, or research chosen to be conducted as a startup.
Level-Intermediate - Mandatory - Third Course to Drive Outcome.
Prerequisites - None, No Coding knowledge necessary, will be built along with the course.
Duration - 36 Hours (6 Hours per week - 2 Hrs x 3)
Assessments - Micro Assessment weekly, Full Assessment last week.

COMBINED LEARNING OUTCOME ACHIEVED

Students should be ready with a compelling technology and use case to take to market and grow with initial interest in the technology from prospective product investors, with compelling business cases, and set goals in traction to meet to proceed.