Our AI & Machine Learning training course in Abu Dhabi is designed to give you a solid foundation in intelligent systems, from theory to practical applications. Whether you're a beginner or a tech professional, this course will help you understand how AI works and how to apply ML algorithms to solve real-world problems.
1. Introduction to Artificial Intelligence & Machine Learning
• Overview of AI, Machine Learning, and Deep Learning.
• Real-world applications in finance, healthcare, and automation.
• Understanding the AI lifecycle and workflow.
2. Types of Machine Learning Algorithms
• Supervised Learning – Regression and classification techniques.
• Unsupervised Learning – Clustering, dimensionality reduction, anomaly detection.
• Reinforcement Learning – Concepts of agents, rewards, and environments.
3. Core ML Concepts & Techniques
• Data preprocessing, feature selection, and data transformation.
• Model training, testing, and validation.
• Understanding overfitting, underfitting, bias-variance tradeoff.
4. Popular ML Algorithms & Implementation
• Linear Regression, Decision Trees, Random Forest, and KNN.
• Naive Bayes, SVM, Gradient Boosting, and XGBoost.
• Implementing models using Scikit-learn, Pandas, and Matplotlib.
5. Introduction to Neural Networks & Deep Learning
• Basics of Perceptrons, Activation Functions, and Backpropagation.
• How Neural Networks relate to ML models.
• Transition into CNNs, RNNs, and LSTMs (Intro level).
6. Natural Language Processing (NLP) & Computer Vision (Intro)
• Text processing, tokenization, and sentiment analysis.
• Basics of image classification and object detection.
• Real-world mini projects using NLP and Vision datasets.
7. AI Ethics, Use Cases & Industry Adoption
• AI in business decision-making and automation.
• Ethical implications, bias in AI, and responsible AI development.
• Case studies from healthcare, finance, retail, and smart cities.
8. Hands-On Projects & Capstone Experience
• Finance: Predicting stock prices or credit scoring using ML.
• Healthcare: Disease prediction using patient data.
• Retail: Customer segmentation and recommendation systems.
• Public Sector: AI for traffic, security, or public services.
By the end of this course, you'll have a strong grasp of AI & ML fundamentals, hands-on coding experience, and the confidence to build intelligent systems or pursue specialized AI roles.