Artificial Intelligence and Machine Learning Course in Dubai
3.5 months of industry-led practical training
Master Python, Pandas, NumPy, and Tableau tools
Learn ML, NLP, and Deep Learning techniques
Work on 5+ industry use cases and a capstone project
Access CareerHub for interviews and resumes
Lifetime access to classes and CareerHub for job readiness
4.8/54632 EnrolledEnrolled Learners
Overview
What our training includes:
- Learn from Middle East industry experts with over 10 years of experience in the tech field
- Apply real-world use cases to grasp AI technologies and their practical applications
- Analyze data statistically using Python libraries like NumPy and Pandas for efficient data handling
- Leverage Matplotlib to create insightful visualizations and explore complex datasets
- Build and implement Machine Learning models for predictive analytics and automation
- Gain conceptual knowledge of CNN & RNN through NLP and Deep Learning applications
- Utilize Tableau for geographical insights, customer behavior analysis, and trend forecasting
Upcoming sessions
Curriculum
1
Evolution of AI: From rule-based systems to deep learning
2
Difference between AI, ML, Deep Learning, and Data Science
3
Business applications across industries (Finance, Healthcare, Retail, Manufacturing, HR)
4
AI/ML project lifecycle and stakeholder management
5
Ethical considerations and responsible AI
1
Understanding structured vs. unstructured data
2
Data quality: The GIGO principle (Garbage In, Garbage Out)
3
Data collection, cleaning, and preprocessing fundamentals
4
Feature engineering basics
5
Data privacy regulations (GDPR, data sovereignty)
1
Types of ML: Supervised, Unsupervised, Reinforcement Learning
2
Common algorithms: Linear Regression, Decision Trees, Random Forest, K-means Clustering
3
Model training, testing, and validation
4
Overfitting vs. Underfitting
1
Introduction to Neural Networks and deep learning
2
Convolutional Neural Networks (CNNs) for image recognition
3
Recurrent Neural Networks (RNNs) for sequence data
4
Natural Language Processing (NLP) basics
5
Transfer learning and pre-trained models
1
Understanding Generative AI: GANs, Transformers, Diffusion Models
2
Large Language Models (LLMs): GPT, BERT, Claude architecture overview
3
Prompt engineering fundamentals
4
Retrieval Augmented Generation (RAG)
5
Business applications: Content creation, code generation, customer service
1
ML project management: From POC to production
2
MLOps: Continuous integration and deployment for ML
3
Model monitoring and maintenance
4
A/B testing and experimentation
5
Building AI teams: Roles and responsibilities
6
Change management for AI adoption
1
AI in Finance: Risk assessment, algorithmic trading, fraud detection
2
AI in Healthcare: Diagnosis, drug discovery, patient care
3
AI in Manufacturing: Quality control, supply chain, predictive maintenance
4
AI in Retail/E-commerce: Personalization, inventory, demand forecasting
5
AI in HR: Recruitment, employee engagement, performance prediction
6
Calculating AI ROI and business impact metrics
1
Each participant/team presents their domain-specific project (15 mins each)
2
Consolidated Project components:
3
Peer and instructor feedback
4
Best project awards
5
Emerging trends: Quantum ML, Edge AI, Federated Learning
6
AI regulation and governance landscape
7
Building a personal AI learning roadmap
8
Resources for continued learning
Meet your Trainer
Our Trainers
Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.
We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.
Learning Objectives
Upon finishing the training, you will excel:
1
Understand the key roles and responsibilities of Data Scientists and AI Engineers
2
Develop expertise in Python libraries, machine learning models, and AI-driven solutions
3
Build predictive models and apply AI techniques to solve real-world challenges
4
Leverage AI tools to analyze data, extract insights, and enhance decision-making
5
Apply a data-driven approach to optimize business processes and improve performance
6
Strengthen your professional portfolio with 5+ industry use cases and a Capstone Project
7
Earn globally recognized Learners Point and KHDA certifications for career advancement
KHDA Certificate
Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.
Learners Point Certificate
Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.
Overall ratings by our students
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Frequently asked questions
The Artificial Intelligence and Machine Learning Course is a training program designed to help professionals and IT enthusiasts with in-demand skills to build intelligent AI systems and data-driven solutions in Dubai and beyond. The training covers core concepts of AI along with ML fundamentals.
There are no eligibility criteria required for the AI and ML course in Dubai. Whether you are an IT professional or a beginner, our course is designed to help you build AI and ML expertise from scratch.
You will learn Python, NumPy, Pandas, MatPlotLib, Seaborn, NLP, Deep Learning, and Machine Learning models, along with hands-on experience in data visualization and AI applications.
Yes, you enrol in the AI and ML Course even if you are located outside UAE. We provide training across GCC regions and guide individuals toward successfully obtaining this valued certification.
Candidates enrolling in our AI and ML course can have a basic programming knowledge, preferably in Python. But our course in Dubai is designed for beginners and provides basic programming concepts before diving into advanced Artificial Intelligence topics.
Our Machine Learning certification is designed to provide theoretical and practical training, with assignments, real-world use cases, and a Capstone Project to ensure complete understanding. Plus, with lifetime access, you can revisit sessions anytime.
AI and ML professionals are in high demand across IT, healthcare, finance, e-commerce, energy, and smart city initiatives in the UAE.
Our CareerHub at Learners Point includes resume building, interview preparation, and job search assistance to help you secure top AI and ML roles in Dubai and beyond.
Yes, there are instalment options available for the fees of the AI and ML course in Dubai. We offer easy instalment plans through Tabby and Tamara as well as No-Cost EMI options with select credit cards.
During the Artificial Intelligence and Machine Learning course in Dubai will complete 5+ industry use cases and a Capstone Project to gain hands-on experience and build a strong portfolio.
The future of Artificial Intelligence (AI) and Machine Learning (ML) will see greater collaboration between humans and AI, offering more personalized experiences in healthcare, education, and creative fields. This will lead to significant economic growth, fueled by increased productivity and innovation.
Key advancements are expected in areas like natural language processing and computer vision. However, challenges like bias, privacy issues, and job displacement will also grow. To unlock AI's full potential and ensure its smooth integration into society, responsible development, strong regulations, and user-friendly platforms for non-experts will be essential.
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