AI GRC | TEQ3

AI Risk and Compliance

Boost your Career with AI Engineering

Join our AI Risk and Compliance Program, an in-depth 3-month course aimed at strengthening your understanding of regulatory frameworks and risk management strategies. Acquire practical experience through case studies and projects, while engaging with a curriculum centered on industry standards and best practices. Stand out to potential employers and boost your prospects of landing a rewarding position in the field.

400 + Learners 4.5+ rATING 80% completion

JOIN THE NEXT COHORT FOR 2025

September Cohort

Start Date: Sept 1, 2025

Virtual
Reserve your Seat

October Cohort

Start Date: Oct 6, 2025

Virtual
Reserve your Seat

November Cohort

Start Date: Nov 3, 2025

Virtual
Reserve your Seat.

December Cohort

Start Date: Dec 1, 2025

Virtual
Reserve your Seat.

RESERVE SEATVIEW BROCHURE

Course Overview

AI Risk and Compliance professionals concentrate on identifying, assessing, and mitigating risks associated with artificial intelligence systems. The curriculum encompasses regulatory frameworks, ethical considerations, risk management strategies, and compliance protocols related to AI technologies. You will learn how to evaluate AI systems for compliance with legal standards and industry best practices. Additionally, you will explore the implications of AI on governance and accountability, gaining a comprehensive understanding of the tools and methodologies that are essential for navigating the evolving landscape of AI risk and compliance.

2000+

Delegates Trained

80%

Completion Rate

4.7+

About the AI Risk and Compliance

Register now View brochure

Pursuing a career in AI Risk and Compliance positions you at the intersection of technology and regulatory frameworks, where you will assess and manage the risks associated with artificial intelligence systems. This vital role is essential across various industries—including finance, healthcare, and technology—and offers significant growth opportunities in an increasingly AI-centric world.

The AI Risk and Compliance Program is tailored to equip aspiring professionals with the knowledge and skills necessary to navigate the complexities of AI governance and compliance. Whether you are starting from scratch or have some prior experience, this program will elevate your understanding to an intermediate-to-advanced level. By the conclusion of the program, you will be adept at identifying potential risks, implementing compliance measures, and understanding the ethical implications of AI technologies.

Throughout this course, you will also gain hands-on experience in risk assessment, regulatory frameworks, and the development of compliance strategies for AI applications. You will learn to advocate for responsible AI practices and ensure that intelligent systems are not only effective but also adhere to legal and ethical standards. You will emerge with the expertise, practical experience, and confidence to take on roles in AI risk management and compliance, making a meaningful impact on your organization’s approach to AI governance. With personalized mentoring and focused job placement assistance, you will be well-equipped to achieve your career goals in the field of AI risk and compliance.

Suitable for;

Data Analysts, Data Scientists, and Software Developers transitioning to AI.

Graduates and professionals seeking a hands-on AI career

Technical professionals from other domains pivoting to AI

Freelancers and consultants wanting to expand their service offering into AI.

This programme is designed to ensure you are job-ready from day one. You will gain the technical depth, practical experience, and confidence required to step directly into an AI Risk and Compliance role — no filler, just focused, industry-backed preparation.

Key Metrics about AI Risk and Compliance

Global Demand

35%

AI Engineering (including model development, deployment, and infrastructure) accounts for 30–35% of the total AI market value, reflecting its core role in delivering AI solutions

In-Demand Roles:

Machine Learning Engineer, AI Developer, NLP Engineer, Computer Vision Engineer, AI Researcher, and AI Architect..

Global AI Market Size

Est. at $300+ billion

Median Salary

US: $135,000–$170,000 UK: £65,000–£95,000

Senior roles can reach $200,000+ with stock options and bonuses.

Global Demand

There has been a 40–50% year-over-year increase in demand for AI Risk and Compliance globally, particularly in sectors like tech, healthcare, finance, manufacturing, and logistics

AI Risk and Compliance View brochure

Foundations of AI & Machine Learning

Gain a foundational understanding of artificial intelligence, its evolution, and current applications. Learn the basics of prompt engineering to effectively interact with large language models (LLMs). This course sets the stage for building intelligent AI systems using natural language instructions.

AI Ethics, Bias & Fairness

Learn the fundamentals of Python — one of the most powerful and versatile programming languages used in data analysis, AI, and software development. This beginner-friendly course covers core concepts like variables, loops, functions, and data structures, providing the essential foundation to build real-world applications and analytical solutions..

AI Risk Management & Governance Frameworks

Learn Python programming from the ground up with a focus on data structures, control flow, and functions. Tailored for beginners, this course provides the coding skills necessary for AI development. You'll also explore Python libraries used in data science and AI.

Regulatory Landscape: EU AI Act, GDPR & Global Standards

Explore supervised and unsupervised learning techniques using Python libraries like Scikit-learn and Pandas. Understand key ML concepts including model training, evaluation, and deployment. This course builds the core skills needed to develop machine learning solutions.

AI Assurance, Audits & Controls

Understand the core architecture behind generative AI and large language models (LLMs). Learn about data pipelines, tokenization, and preprocessing techniques essential for training and fine-tuning models. This course bridges foundational theory with practical data prep.

Building Internal AI Governance Programs

Study foundational NLP models like BERT, GPT, and T5, and how they power modern language understanding. Learn how to apply these models for text classification, summarization, and sentiment analysis. Emphasis is placed on using pre-trained models effectively.

This programme is designed to ensure you are job-ready from day one. You will gain the technical depth, practical experience, and confidence required to step directly into an AI Risk and Compliance role — no filler, just focused, industry-backed preparation

Learning Outcome

Upon successful completion of this programme, you will be able to demonstrate advanced skills and experience in developing and deploying AI Engineering Model for showcasing to hiring managers and impressing employers:

Understand Core AI Concepts

Build AI and ML Models

Apply Prompt Engineering

Work with Generative AI

Implement NLP Solutions

Data Project management

Develop AI Agents with LangChain & RAG

Manage AI Projects

Introduction to Analytics

This course will introduce you to the world of Big Data and Analytics, showing you the entire Ecosystem in the Big Data World

Business Analytics with Excel

Participants will gain proficiency in using Excel for data analysis and reporting. The course will cover advanced Excel functions, data manipulation, and the creation of dynamic reports and dashboards to support business decision-making

Developing Queries with Microsoft SQL

This course will teach delegates how to write and optimize SQL queries to extract and manipulate data from relational databases. Participants will learn about database structures, query syntax, and best practices for efficient data retrieval

Data Analysis and Visualization with PowerBI

Attendees will learn how to use PowerBI to transform raw data into insightful visualizations and interactive dashboards. The course will cover data import, cleaning, modeling, and the creation of various types of visual reports to communicate data effectively. .

Introduction to Descriptive and inferential Statistics

Delegates will explore the basics of statistical analysis, including descriptive statistics to summarize data and inferential statistics to draw conclusions and make predictions. The course will cover key concepts such as probability, hypothesis testing, and regression analysis.

Introduction to Python Programming

Participants will be introduced to Python programming for data analysis. The course will cover fundamental programming concepts, data structures, and libraries such as Pandas and NumPy, enabling delegates to perform data manipulation and analysis efficiently

Storytelling with Powerpoint

This course will teach delegates how to effectively communicate data insights through compelling presentations. Participants will learn techniques for designing clear and engaging slides, structuring narratives, and using visual aids to support their stories

Collateral Development and Management Reporting with Powerpoint

Capstone Projects

Delegates will be given a minimum of two industry work Experience projects

Introduction to Analytics

This course will introduce you to the world of Big Data and Analytics, showing you the entire Ecosystem in the Big Data World