Course Information

Introduction

Python has emerged as one of the most popular programming languages for Artificial Intelligence (AI) due to its simplicity, flexibility, and extensive library support. This course, "Programming for AI with Python," is designed to provide participants with a comprehensive understanding of how Python can be leveraged to develop intelligent systems and solve real-world problems. The course bridges the gap between theoretical knowledge and practical applications, ensuring participants gain both foundational and advanced insights into programming for AI.

Participants will explore the key concepts of AI, machine learning, and deep learning while mastering Python’s essential tools and frameworks, including NumPy, pandas, TensorFlow, Keras, and scikit-learn. The course emphasizes hands-on experience, empowering learners to implement AI solutions through guided coding exercises, project-based learning, and case studies.

The curriculum also highlights the importance of structuring AI projects effectively, starting with problem definition, data preparation, model building, and evaluation. Through step-by-step instruction, participants will build skills in designing robust machine learning pipelines and deploying AI solutions to production environments.

A significant aspect of the course is dedicated to exploring ethical considerations, ensuring that AI systems are developed responsibly. Participants will learn how to address challenges such as bias in AI models, data privacy, and transparency in decision-making. By combining technical expertise with ethical awareness, learners will be equipped to create AI solutions that align with industry standards and societal expectations.

Whether participants are new to AI programming or have some experience in Python, the course ensures a progressive learning journey. With practical assignments, group discussions, and expert guidance, learners will develop the confidence to tackle complex AI programming tasks independently.

The course's dynamic approach aims to cater to diverse professional needs, making it an essential program for anyone seeking to excel in AI programming and stay ahead in the rapidly evolving technological landscape.

Objectives

By attending this course, participants will be able to:

Understand the fundamentals of Python programming and its relevance to AI development.
Explore the core concepts of AI, machine learning, and deep learning and their practical applications.
Utilize Python libraries such as NumPy, pandas, scikit-learn, TensorFlow, and Keras to build AI models.
Develop skills in data preprocessing, feature engineering, and data visualization for AI projects.
Build and evaluate machine learning pipelines for classification, regression, clustering, and deep learning tasks.
Gain insights into deploying AI models in production environments using best practices.
Address ethical considerations in AI programming, including fairness, transparency, and accountability.
Work on real-world projects to reinforce learning and apply knowledge to industry-relevant scenarios.

Who Should Attend?

This course is ideal for:

Professionals aspiring to build a career in Artificial Intelligence and Machine Learning.
Data scientists, software developers, and IT professionals seeking to enhance their AI programming skills.
Individuals with basic programming knowledge looking to transition into the field of AI.
Business analysts and project managers involved in AI-driven projects.
Researchers and academics interested in applying AI techniques using Python.
Students and graduates eager to gain practical AI programming experience to boost their career prospects.

Training Method

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a 7” Tablet containing a copy of the presentation, slides and handouts
• Post-assessment

Program Support

This program is supported by:
* Interactive discussions
* Role-play
* Case studies and highlight the techniques available to the participants.

Daily Agenda

Daily Schedule (Monday to Friday)
- 09:00 AM – 10:30 AM Technical Session 1
- 10:30 AM – 12:00 PM Technical Session 2
- 12:00 PM – 01:00 PM Technical Session 3
- 01:00 PM – 02:00 PM Lunch Break (If Applicable)
- Participants are expected to engage in guided self-study, reading, or personal reflection on the day’s content. This contributes toward the CPD accreditation and deepens conceptual understanding.
- 02:00 PM – 04:00 PM Self-Study & Reflection

Please Note:
- All training sessions are conducted from Monday to Friday, following the standard working week observed in the United Kingdom and European Union. Saturday and Sunday are official weekends and are not counted as part of the course duration.
- Coffee and refreshments are available on a floating basis throughout the morning. Participants may help themselves at their convenience to ensure an uninterrupted learning experience Provided if applicable and subject to course delivery arrangements.
- Lunch Provided if applicable and subject to course delivery arrangements.