Part Two

INTRODUCTION TO Artificial Intelligence

Embark on a fascinating exploration of Artificial Intelligence (AI), a transformative force that reshapes how we live, work, and solve complex problems. This section offers an introduction to AI, demystifying its concepts, technologies, and real-world applications. Designed for those new to the field as well as those looking to deepen their understanding, we cover the foundational elements that make AI one of the most exciting and rapidly evolving areas of study and innovation today.

 

Artificial Intelligence seeks to create machines capable of intelligent behaviour, from understanding natural language to recognising patterns and making decisions. Through this introductory module, you will gain insights into the history of AI, its development, and its future potential to augment human capabilities across various domains, including healthcare, automation, and beyond.

 

You will delve into different branches of AI, including machine learning, deep learning, robotics, and natural language processing. We will explore how key algorithms enable machines to learn from data, adapt to new situations, and perform tasks traditionally requiring human intelligence. By understanding the principles and ethical considerations of AI, you'll be better equipped to harness its power responsibly and creatively.

 

This introduction aims to ignite your curiosity and provide the tools to navigate the complexities of artificial intelligence. As AI continues to advance, the knowledge and skills acquired here will prepare you for the exciting challenges and opportunities that lie ahead in the AI-driven future.

Timetable

 

 Monday

11 Mar 24

Tuesday

12 Mar 24

Wednesday

13 Mar 24

Thursday

14 Mar 24

Friday

15 Mar 24

Saturday

16 Mar 24

Asynchronous:

Self paced learning facilitated by following the supplied course materials and reading.

17:30 (IST)

12:00 (GMT)

Release of online learning resources for PartTwo.

________________

 

Milestone 3:

Key objectives review

Self paced study

Milestone 4:

Key objectives review

 

Self paced study

Self paced study

Milestone 5:

Key objectives review

 

Self paced study

 

Synchronous:

These are the tutor led live sessions. Use the provided Zoom links to join.

15:00 - 16:30 (IST)

09:30 - 11:00 (GMT)

 

Workshop 2: Data Science

 

 

Zoom (D) classroom link in Part One

 

Session Recording

18:00 - 18:30 (IST)

12:30 - 13:00 (GMT)

 

Optional drop-in session

 

 

Zoom (E) classroom link below

15:00 - 16:30 (IST)

09:30 - 11:00 (GMT)

 

Workshop 3: Artificial Intelligence

 

 

Zoom (F) classroom link below

 

Session Presentation (video)

Session Discussion (video)

 

15:00 - 16:30 (IST)

09:30 - 11:00 (GMT)

 

Workshop 4: Artificial Intelligence

 

 

Zoom (G) classroom link below

 

Session Recording

 

Evaluation / Assessment

     

Evaluation

Start your Part two learning

Learning Resources

Click the button below to begin the self-paced learning for Part Two.

ZOOM CLASSROOM LINKS

Zoom (E)

Topic: Optional support drop-in session
Attendance: Optional
Time: Mar 12, 2024 6:00pm (IST) 12:30pm (GMT)
Join Zoom Meeting
Ended
Meeting ID
Passcode: ------

 

Zoom (F)

Topic: Workshop 3: Artificial Intelligence
Attendance: Required
Time: Mar 13, 2024 3:00pm (IST) 9:30am (GMT)
Join Zoom Meeting
Ended
Meeting ID
Passcode: ------

Workshop 3 video recording: Workshop 3 Presentation

Workshop 3 video recording: Workshop 3 Discussions

 

Zoom (G)

Topic: Workshop 4: Artificial Intelligence
Attendance: Required
Time: Mar 15, 2024 3:00pm (IST) 9:30am (GMT)
Join Zoom Meeting
Ended
Meeting ID
Passcode: ------

Workshop 4 video recording: Workshop 4 Presentation