AI_Engineer

AI Engineer Programme

Boost your Career with AI Engineering

Join our AI Engineer Program, a comprehensive 3-month course designed to enhance your technical skills and communication abilities. Gain hands-on experience through practical projects, and benefit from a curriculum focused on real-world applications. Impress potential employers and increase your chances of securing a job with a competitive salary.

400 + Learners 4.5+ rATING 80% completion

JOIN THE NEXT COHORT FOR 2025

September Cohort

Start Date: Sept 1, 2025

Virtual
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October Cohort

Start Date: Oct 6, 2025

Virtual
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November Cohort

Start Date: Nov 3, 2025

Virtual
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December Cohort

Start Date: Dec 1, 2025

Virtual
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Course Overview

Artificial Intelligence Engineers focus on computer programming, data modelling and evaluation strategies, data, statistics and algorithms, machine learning algorithms and deep learning applications. Course content covers data-driven AI technologies such as machine learning, deep learning, and reinforcement learning, then teaches you how to build and use AI tools. You will then see how AI is poised to impact the IT industry you work in, and you will fully understand AI and all the specific technology, tools and trends is driving today’s AI revolution.

2000+

Delegates Trained

80%

Completion Rate

4.7+

About the AI Engineer Programme

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Becoming an AI Engineer enables you to be at the forefront of technological innovation by designing, building, and deploying intelligent systems that solve real-world problems. This high-impact career path offers opportunities across diverse sectors—from healthcare to finance to robotics—and promises excellent growth potential in today’s AI-driven economy.

The AI Engineer Job Focus Program is designed to equip aspiring professionals with the technical and strategic skills required to thrive in artificial intelligence and machine learning roles. Whether you're a beginner or have some foundational knowledge, this program will guide you toward an intermediate-to-advanced level of proficiency. By the end of the program, you will be able to build and deploy machine learning models, understand the architecture of large language models (LLMs), and develop AI-powered applications using tools like Python, TensorFlow, Keras, and LangChain..

Through this course, you'll also gain practical experience in prompt engineering, model fine-tuning, and leveraging AI agents in real-world applications. You will learn to implement responsible AI practices and develop intelligent systems that are scalable, ethical, and effective. You'll emerge with the knowledge, experience, and confidence to take on roles in AI engineering and contribute meaningfully to your organization’s innovation journey. Supported by personalized mentoring and targeted job placement support, you’ll be well-prepared to reach your highest career aspirations in the field of artificial intelligence..

Suitable for;

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

STEM 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 Engineer role — no filler, just focused, industry-backed preparation.

Key Metrics about AI Engineering

Global Demand for AI Engineer

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 AI Engineer Market Snapshot:

In 2024, the global AI engineering services market was worth between USD 12–16 billion.
By 2025, estimates suggest growth to USD 17–22 billion, increasing further to ~USD 87 billion by 2030 and potentially USD 280 billion by 2034, with a robust 33–40% annual growth rate.
This reflects explosive investment in AI development, deployment, and professional services—directly fueling the demand for skilled AI engineers.

Global Demand

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

AI Engineering Courses View brochure

Introduction to Artificial Intelligence

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.

Introduction to Python

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..

Machine Learning with Python

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.

Introduction to Deep Learning & Neural Networks with Keras and Tensorflow

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.

Generative AI and LLMs: Architecture and Data Preparation

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.

Gen AI Foundational Models for NLP & Language Understanding

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.

Generative AI Language Modeling with Transformers

Explore transformer architectures that drive cutting-edge AI applications. Build and fine-tune generative models using frameworks like Hugging Face. Gain experience generating text, code, and other outputs from trained language models.

Fundamentals of AI Agents Using RAG and LangChain

Learn how to build AI agents using Retrieval-Augmented Generation (RAG) and LangChain. This course covers chaining prompts, document loaders, memory management, and retrieval strategies. You'll gain hands-on experience with building intelligent, context-aware agents.

Data Engineering for AI Engineers

Participate in an extensive Data Engineering for AI Engineer course that equips you with essential skills in data management, processing, and analysis. Learn to design and implement robust data pipelines using tools like Apache and Airflow, ensuring seamless integration of data for AI applications. This course prepares you for critical roles in AI development by emphasizing practical techniques and real-world scenarios.

AI Deployment with Cloud & DevOps

In this AI Deployment with Cloud & DevOps course, you will learn to leverage Streamlit and Flask to create interactive web applications powered by AI. Gain hands-on experience deploying your projects on leading cloud platforms like AWS and GCP. This course will equip you with the skills to build, deploy, and manage AI applications in a cloud environment, preparing you for a successful career in AI engineering and DevOps.

Al Ethics, Security & Governance

Explore the critical aspects of AI Ethics, Security, and Governance in this course. Delve into the ethical implications of AI technologies, understand the importance of data privacy and security, and learn about the frameworks and policies that govern AI deployment. This course equips you with the knowledge to navigate the complex landscape of AI responsibly and prepares you for roles that require a strong ethical foundation in technology.

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 Engineer 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