Course Overview

“The key to artificial intelligence has always been the representation.”

—Jeff Hawkins

The simulation of human intellect by machines is known as “artificial intelligence”, machines that display human characteristics such as learning, problem-solving and decision making. AI aims to build smart machines capable of performing tasks that generally require human intelligence. AI typically refers to a broader concept where the idea is that machines can execute tasks smartly.  While machine learning is a sub field of AI  that gives machines the ability to learn and adapt through experience.

In today’s world, firms that want to gain a competitive advantage employ various kinds of artificial intelligence to better understand their consumers and to increase their knowledge of a customer’s needs.

This diploma in Artificial Intelligence delves into Expert systems, Machine Learning, Deep learning, Reinforcement learning, Data Mining, and Statistics. Using technologies such as Python, it walks a business through all the steps, from model training to deploying models into production that is required to begin leveraging the potential of AI. It also explores the future possibilities and challenges of AI.

Course Modules

AI Foundations (3 weeks)

  • History of AI
  • Current state-art-of-the AI tools
  • Application of AI
  • Knowledge Representation and Reasoning in context to Artificial Intelligence
  • Expert Systems
  • Search Strategies in AI
  • Small live Demo of AI application
  • Introduction to Explainable AI
  • Future of AI
  • Lab Exercise

Advanced Concepts in AI and ML (2 weeks)

  • Theory of Types of Data
  • Exploratory Data Analysis Theory
  • Supervised and Unsupervised Learning techniques
  • Crash Course of python / Python essentials
  • Introduction to the tools like Panda’s profiling and D tale
  • Exploratory Data Analysis (Demonstrations)
  • Automated features extractions
  • Lab Exercise

Applied Machine Learning and Advance Selected topics (2 weeks)

  • Machine learning Algorithms
  • Evaluation of ML project
  • Deployment of the Model
  • Introduction to Deep learning
  • Introduction to reinforcement learning
  • Introduction to Model Optimization Techniques
  • Artificial Neural Networks
  • Lab Exercise

Projects (3 weeks)

  • Sentiment Analysis (theory and practical)
  • Image Classification (theory and practical)
  • Intelligent Conversational Chatbot (theory and practical)
  • Predictive Modelling (Classification and Regression (theory and practical)
  • Lab Exercise

*Course content is indicative and subject to the student learning rate.

Learning Outcomes

Learners will be able to illustrate how artificial intelligence, in the form of applied machine learning and deep learning, can be incorporated into their individual organizations through this curriculum. It will guide them through the process of obtaining data, utilizing it to train models, and incorporating these models into the organization’s infrastructure to reap the benefits of artificial intelligence. This credential is intended for students who come from non-cognate backgrounds and have no technical expertise, as well as those who come from cognate backgrounds but lack technical skills and knowledge.

Course Award

A City College’s Professional Diploma Course is a focused, practical programme designed and delivered by an industry practitioner, that consolidates, upskills or reskills learners in a professional area. They are stand-alone qualifications that indicate that you have been trained in a particular area or specific subject matter.

City College Diplomas are suitable for career minded learners wishing to advance their professional skills and prospects. They are widely accepted by employers and many students are sponsored to study here by their organisation.


Dr. Abhishek Kaushik is a post-doctoral research fellow and Senior Industry Consultant (Artificial intelligence). He is currently working with UCD and Industrial partners to build the REG Tech system with machine learning and reinforcement learning. He has lectured in multiple Irish educational institutions.

He is one of the few Ph.D. students who completed in less than four years from Adapt Centre, Dublin City University. He received his master’s degree in Information Technology from Kiel University of Applied Science (Germany) in 2016, and his bachelor’s degree in Computer Science and Engineering from Kurukshetra University (India) in 2012. His research focuses on | NLP | Conversational Search | Bot | Machine Learning | Deep Learning | Information Retrieval | Reinforcement Learning | User Behaviour | Reg Tech | Legal System | Explainable AI |. He has also published some outstanding research work in collaboration with UCD and DCU.

He has gained about five years of experience in Industrial Research while working in Ireland, Germany, and India. He has been awarded multiple grants and scholarships during his research journey by various funding agencies. He has participated in many research talks in esteemed universities all around the globe (Canada, UK, US, India, etc). He is an active reviewer of numerous journals and conferences. He wrote multiple chapters focussing on applications of AI published by springer.


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Live online training with real-time instructor-student interaction.
  • Live & fully online
  • Archived for review
January 2023
10 weeks, 1 evening per week from 6.30 to 9.30pm GMT
Study in a classroom environment one evening a week.
  • City centre location
  • Fully interactive
  • Limited class sizes
January 2023
10 weeks, 1 evening per week from 6.30 to 9.30pm GMT

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