Artificial Intelligence (Level 6)

COURSE DESCRIPTION

Dive into the forefront of technology with Artificial Intelligence, a program crafted for aspiring innovators ready to shape the future of intelligent systems. This course blends advanced machine learning, ethical AI design, and real-world applications to empower you to create transformative solutions for industries ranging from healthcare to finance.

Through hands-on projects, cutting-edge tools, and collaborative labs, you’ll master deep learning, natural language processing, and computer vision while addressing ethical and societal implications. Develop AI models using frameworks like TensorFlow and PyTorch, and tackle live industry challenges in partnership with tech firms. Showcase your work in a capstone project presentation attended by AI industry leaders.

CERTIFICATION

National Diploma/ CPA II/ Master Crafts Person II

ENTRY REQUIREMENTS

KCSE Mean Grade C-

Level 5 Qualification

DURATION

24 Months

LEARNING OUTCOMES

• Lead Interdisciplinary AI Projects: Direct collaborative AI projects with industry partners, integrating cross-disciplinary insights to deliver innovative, market-ready solutions under professional constraints.

• Apply Natural Language Processing Techniques: Build and deploy sophisticated NLP systems for tasks such as sentiment analysis, text generation, and conversational AI, ensuring robust and scalable solutions.

• Create Computer Vision Applications: Develop advanced computer vision systems for applications like object detection, image classification, and autonomous navigation, leveraging cutting-edge algorithms and tools.
• Master Data Engineering for AI: Develop advanced skills in data acquisition, cleaning, transformation, feature engineering, and pipeline optimization for large-scale AI datasets, ensuring data quality and usability.
• Lead AI Project Development: Demonstrate leadership in managing the lifecycle of AI projects, including requirement gathering, solution architecture, team coordination, and strategic communication with stakeholders.
• Communicate Complex AI Concepts: Effectively communicate highly technical AI concepts, methodologies, and findings to both technical and non-technical audiences

• Analyze and Interpret Data for AI: Utilize advanced data analysis techniques to preprocess, interpret, and visualize complex datasets, enabling effective AI model training and performance evaluation.

• Develop Advanced AI Models: Design, implement, and optimize complex machine learning and deep learning models using frameworks like TensorFlow and PyTorch to solve real-world problems in diverse industries.