AI & Machine Learning for Real-World Applications

Course Introduction

Artificial Intelligence (AI) and Machine Learning (ML) are transforming industries by enabling machines to make intelligent decisions and automate complex tasks. This hands-on course provides a solid foundation in AI/ML concepts and applications, equipping participants with the skills needed to design, build, and deploy real-world machine learning models using tools like Python, Scikit-learn, and TensorFlow.

Participants will explore both the theoretical foundations and practical aspects of AI/ML, including data preprocessing, algorithm selection, model training, evaluation, and deployment.

After Study Job Opportunities

• Machine Learning Engineer
• AI Developer
• Data Scientist
• Data Analyst
• Business Intelligence Engineer
• AI/ML Consultant
• Research Assistant in AI
• AI Product Developer

List of Required Documents

• Resume
• Passport or ID Photo

Admission Tests

• Study of the school file
• Tests: general knowledge, English, logic and practical case study
• Individual motivational interview

Professional Training

This course emphasizes:

• Practical understanding of supervised and unsupervised ML techniques
• Real-world problem-solving using machine learning
• Hands-on coding in Python using industry-standard libraries
• Model evaluation, tuning, and deployment
• Application of AI across sectors such as healthcare, finance, telecom, and manufacturing

Objectives and Context of Certification

By the end of the course, participants will understand the core principles of AI and ML, be able to preprocess, clean, and analyze datasets, choose appropriate ML algorithms based on data and use cases, train, test, and evaluate machine learning models, use frameworks such as Scikit-learn and TensorFlow for implementation, understand ethical considerations and challenges in deploying AI models, and earn a certificate validating their practical knowledge of AI/ML. The certification positions learners for jobs in fast-growing AI/ML domains and serves as a strong foundation for further study or specialization.

Graduate Responsibilities

After completing the training, participants will be able to:

• Apply AI/ML techniques to solve business and technical problems
• Collaborate with cross-functional teams on data-driven projects
• Continuously evaluate and improve machine learning models
• Maintain ethical standards in the development and deployment of AI
• Stay updated with the latest trends and tools in AI/ML

Post-Study Job Opportunities

Graduates can work in industries such as IT, Healthcare, Telecom, Finance, E-commerce, and Manufacturing. Roles include Data Scientist, ML Engineer, AI Systems Analyst, and Predictive Analyst in domains such as NLP, Computer Vision, Predictive Modeling, and Recommendation Systems.

Evaluation Methodology

• Weekly Quizzes (20%) – Understanding of key concepts
• Hands-on Assignments (30%) – Application to practical scenarios
• Final Project / Mini Capstone (30%) – Cumulative understanding project
• Participation & Interaction (10%)
• Final Assessment Test (10%) – Summary of key takeaways

Course Summary

• Duration: 2 weeks (60 hours) or part-time: 80 hours over 8 weeks
• Format: Online / In-person / Hybrid (ILT)
• Modules Include: Supervised and Unsupervised Learning, Python for ML, Model Evaluation, Deployment, Ethics in AI
• Assessment: Hands-on coding exercises, projects, and final evaluation
• Outcome: Professional certification in AI and Machine Learning for Real-World Applications

This course provides a practical foundation in AI/ML, enabling participants to build and deploy intelligent systems for real-world use cases.

Starting intake: According to customer request

Tuition Fees:

• €3,000 per participant (60 hours)
• Inhouse corporate training: €30,000 per cohort (10-15 participants)