Artificial Intelligence Course Overview
| Course Hours | 60 hours |
| No of People in a Batch | 6 People/ Batch |
| Accreditations | AI CERT |
| Trainer Availability |
Week Days: 11:00 AM - 8:00 PM
Weekends: 9:00 AM - 6:00 PM
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| Corporate Training Days | 8 Days |
| Course Fee | 3500 AED |
| Modes of Training | Online/ Classroom / At a Star Hotel (For Corporate Batches Only) |
What You'll Learn From Artificial Intelligence Course?
- Python Programming Fundamentals
- Data Analysis and Visualisation
- Machine Learning Foundations
- Natural Language Processing Basics
- Neural Network Implementation
- Practical AI Project Development
About Our Artificial Intelligence with Python Course in Dubai
The Artificial Intelligence with Python course in Dubai offers a comprehensive 60-hour training program by Edoxi. This course is designed for both beginners and experienced IT professionals. Our AI course integrated with Python helps you effectively utilise AI technologies across various industries, including finance and healthcare.
We built the curriculum around 18 modules, ensuring that you don’t need any prior programming knowledge. Our dynamic AI course is led by an expert trainer with over 12 years of industry experience. We balance theoretical insights with practical applications through interactive coding and problem-solving exercises.
You can conveniently attend classes from Monday to Thursday and on Saturday from 11:00 AM to 8:00 PM, with Sunday sessions running from 9:00 AM to 6:00 PM. We reserve Fridays for breaks, making it easier for both working professionals and full-time learners to participate.
We emphasise nurturing analytical thinking and communication skills, critical for success in data science and AI careers. Our detailed presentations and study guides cover everything from foundational concepts to advanced topics, equipping you with the knowledge and skills to achieve your technical aspirations. The course will provide practical experience with tools such as Jupyter Notebook, Pandas, and NumPy, preparing you for roles in top UAE AI companies like Emirates AI and PAX AI.
Whether you're interested in automation, data-driven decision-making, or emerging technologies, our structured pathway will help you turn your technical aspirations into practical expertise. Get started now!
Artificial Intelligence with Python Course Features
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Personalised Learning Options
You can choose between personalized one-on-one sessions or small group training (4-6 students), ensuring focused attention and interactive learning.
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Practical Project Portfolio
You will engage in mini-projects that involve data handling, machine learning models, and neural networks to build a portfolio showcasing your skills.
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Comprehensive Study Materials
You will have access to detailed presentations and PDF notes designed to support both in-class learning and self-study.
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Multiple Training Formats
You can choose between in-person training at our Dubai facility or online sessions according to your preference.
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Interactive Coding Environment
You will have the chance to work in industry-standard development environments, ensuring you gain practical programming experience.
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Professional Assessment & Certification
You will receive Edoxi’s course completion certificate after successfully passing the post-course assessment.
Who Can Join?
- Fresh Graduates & STEM Professionals: Recent graduates in Computer Science, IT, Engineering, Mathematics, or any related discipline looking to start their career in AI and data science.
- Software Developers & IT Professionals: Programming professionals seeking to expand their expertise into AI and machine learning, leveraging their existing development skills.
- Business & Analytics Professionals: Business analysts, data analysts, and professionals from finance or healthcare sectors want to integrate AI capabilities into their work.
- Career Transitioners: Professionals from any background with analytical thinking abilities and basic familiarity with programming concepts are ready to embrace AI technology.
- Corporate Teams: Organizations looking to upskill their technical teams with practical AI knowledge and Python programming capabilities.
- Self-Learners & Tech Enthusiasts: Individuals passionate about emerging technologies and automation, with a drive for problem-solving and data-driven decision-making.
Artificial Intelligence with Python Course Modules
- Module 1: Introduction to Python
- Chapter1.1: Python Fundamentals
- Lesson 1.1.1: Overview of Python and its features
- Lesson 1.1.2: Setting up the Python development environment
- Chapter 1.2: Programming Basics
- Lesson 1.2.1: Python syntax and basic structure
- Lesson 1.2.2: Writing and running Python programs
- Module 2: Variables, Data Types and Operators
- Chapter 2.1: Working with Data Types
- Lesson 2.1.1: Working with variables and data types (numbers, strings, booleans)
- Lesson 2.1.2: Type conversion and casting
- Chapter 2.2: Understanding Operators
- Lesson 2.2.1: Arithmetic, assignment, comparison and logical operators
- Module 3: Control Flow and Loops
- Chapter 3.1: Conditional Programming
- Lesson 3.1.1: Conditional statements (if/else, Elif)
- Lesson 3.1.2: Breaking and continuing loop execution
- Chapter 3.2: Loops and Iteration
- Lesson 3.2.1: Looping structures (for, while)
- Lesson 3.2.2: Working with lists and iterating over them
- Module 4: Functions and Modules
- Chapter 4.1: Function Fundamentals
- Lesson 4.1.1: Creating and invoking functions
- Lesson 4.1.2; Function parameters and return values
- Chapter 4.2: Module Management
- Lesson 4.2.1: Variable scope and global keyword
- Lesson 4.2.2: Importing and using modules in Python
- Module 5: Strings and File Handling
- Chapter 5.1: String Operations
- Lesson 5.1.1: Manipulating strings (concatenation, slicing, formatting)
- Chapter 5.2: File Operations
- Lesson 5.2.1: Reading from and writing to files
- Lesson 5.2.2: Opening, closing, and deleting files
- Lesson 5.2.3: File permissions and error handling
- Module 6: Data Structures
- Chapter 6.1: Basic Data Structures
- Lesson 6.1.1: Working with lists, tuples, and dictionaries
- Lesson 6.1.2: Accessing and modifying elements in data structures
- Chapter 6.2: Advanced Data Structure Operations
- Lesson 6.2.1: Iterating and manipulating data structures
- Lesson 6.2.2: Working with sets and frozen sets
- Module 7: Object-Oriented Programming (OOP) in Python
- Chapter 7.1: OOP Concepts
- Lesson 7.1.1:Introduction to OOP concepts (classes, objects, methods, attributes)
- Lesson 7.1.2: Creating and using classes in Python
- Chapter 7.2: OOP Implementation
- Lesson 7.2.1: Encapsulation, inheritance, and polymorphism
- Lesson 7.2.2: Working with Objects and Class Relationships
- Module 8: File Input/output (I/O) and Serialization
- Chapter 8.1: File Handling
- Lesson 8.1.1:Reading and writing data from/to files
- Chapter 8.2: Data Serialization
- Lesson 8.2.1: Serialization and deserialization of objects (pickle, JSON, CSV)
- Lesson 8.2.2: Working with CSV and JSON files
- Module 9: Regular Expressions
- Chapter 9.1: Regex Basics
- Lesson 9.1.1: Introduction to regular expressions
- Lesson 9.1.2: Using regular expressions for pattern matching and search
- Chapter 9.2: Text Processing
- Lesson 9.2.1: Validating and manipulating text using regular expressions
- Module 10: Introduction to Python Libraries and Frameworks
- Chapter 10.1: Python Ecosystem
- Lesson 10.1.1: Overview of popular Python libraries and frameworks
- Chapter 10.2: Applications
- Lesson 10.2.1: Introduction to data analysis, scientific computing, and web development with Python
- Module 11: Working with Data
- Chapter 11.1: Data Analysis Fundamentals
- Lesson 11.1.1: Introduction to data analysis with pandas
- Lesson 11.1.2: Dataframes: creation, manipulation, and analysis
- Chapter 11.2: Data Visualization
- Lesson 11.2.1: Basic data visualization with Matplotlib
- Module 12: Introduction to Artificial Intelligence
- Chapter 12.1: AI Fundamentals
- Lesson 12.1.1: Definition and history of AI
- Lesson 12.1.2: Types of AI: Narrow AI vs General AI
- Chapter 12.2: Industry Applications
- Lesson 12.2.1: AI applications in various industries
- Module 13: Introduction to Machine Learning
- Chapter 13.1: ML Basics
- Lesson 12.1.1: Basics of Machine Learning
- Lesson 12.1.2: Supervised and Unsupervised Learning
- Lesson 12.1.3: Data Preparation and Preprocessing
- Chapter 13.2: Data Processing
- Lesson 13.2.1: Importance of data in AI
- Lesson 13.2.2: Data cleaning and preprocessing techniques
- Lesson 13.2.3: Handling missing values, normalization, and standardization
- Module 14: Supervised Learning - Regression
- Chapter 14.1: Basic Regression Techniques
- Lesson 14.1.1: Simple Linear Regression
- Lesson 14.1.2: Multiple Linear Regression
- Lesson 14.1.3: Polynomial Regression
- Chapter 14.2: Advanced Regression
- Lesson 14.2.1: Decision Tree Regression
- Lesson 14.2.2: Random Forest Regression
- Lesson 14.2.3: Regression Model Selection
- Lesson 14.2.4: Evaluating Regression Model
- Module 15: Supervised Learning - Classification
- Chapter 15.1: Classification Fundamentals
- Lesson 15.1.1: Logistic Regression
- Lesson 15.1.2: K-Nearest Neighbour (k-NN)
- Chapter 15.2: Model Evaluation
- Lesson 15.2.1: Classification Model Selection
- Lesson 15.2.: Evaluating Classification Model
- Module 16: Unsupervised Learning - Clustering
- Chapter 16.1: Clustering Basics
- Lesson 16.1.1: Introduction to clustering
- Chapter 16.2: Clustering Techniques
- Lesson 16.2.1: k-Means clustering
- Lesson 16.2.2: Hierarchical Clustering
- Module 17: Natural Language Processing (NLP)
- Chapter 17.1: NLP Fundamentals
- Lesson 17.1.1: Introduction to NLP
- Lesson 17.1.2: Types of NLP
- Chapter 17.2: Implementation
- Lesson 17.2.1 • Classical vs Deep Learning Model
- Lesson 17.2.2 • Natural Language Processing in Python
- Module 18: Deep Learning
- Chapter 18.1: Neural Networks
- Lesson 18.1.1: Artificial Neural Networks
- Chapter 18.2: Advanced Neural Networks
- Lesson 18.2.1: Convolutional Neural Network
Projects and Case Studies on Artificial Intelligence with Python Course
- Project 1: Predicting Housing Prices:
Build a machine learning model using Python to predict housing prices based on historical data. This project will help you apply concepts of data preprocessing, regression, and evaluation of machine learning models. - Project 2: Customer Segmentation Using Clustering
Perform customer segmentation by building an unsupervised learning model using k-means clustering. You will work with real-world datasets to categorize customers based on purchasing behaviours. - Project 3: Image Classification Using Deep Learning
Create a convolutional neural network (CNN) to classify images. This project will give you hands-on experience with deep learning using TensorFlow and Keras. - Case Study1: AI Implementation for Retail Demand Forecasting
A retail company used AI models developed by one of our course participants to accurately forecast product demand. The company saw a 20% reduction in overstock and understock scenarios, optimising its supply chain management.
Course Outcome
After completing Edoxi's AI training in Dubai you will:
- Develop a strong foundation in Python programming, which is essential for AI development.
- Gain knowledge of fundamental AI principles, including machine learning, deep learning, and natural language processing.
- Learn to apply AI techniques to real-world problems.
- Learn how to manipulate and analyse data using libraries like
- Pandas and NumPy, which are crucial for effective AI modelling.
Be able to design, implement, and evaluate AI models using frameworks such as TensorFlow or PyTorch. - Develop critical thinking and problem-solving skills, enabling you to tackle complex business challenges with AI solutions.
- Prepared for roles in AI development, data analytics, and machine learning engineering, with a unique blend of technical skills and industry knowledge.
- Engage with industry professionals and peers which leads to valuable connections in the AI and tech community.
- Receive a salary that meets industry standards.
Average Monthly Salary for AI Developers
| Entry-level Job Designations | Average Monthly Salary (in AED) |
| Data Analyst | 5,000 - 10,000 |
| Data Science Associate | 6,000 - 12,000 |
| Associate ML Engineer | 7,000 - 14,000 |
| Associate Data Analytics Developer | 6,500 - 13,000 |
| Associate NLP Engineer | 7,500 - 15,000 |
| AI Research Assistant | 5,500 - 11,000 |
| Junior Python Developer | 5,000 - 10,000 |
*Note: These salary ranges are compiled through comprehensive research including professional salary websites (UAESalary.com, SalaryExpert.com, PayScale.com) and insights from industry professionals in UAE. Figures are indicative and vary based on factors like qualifications, certifications, technical skills, company size, and experience. Subject to change according to market conditions.
Top Companies Hiring AI Developers
- Accenture
- Amazon
- Builder.ai
- Segula Technologies
- IBM
- IIQAF Group
How To Get Certified in Edoxi’s AI Course?
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Why Choose Edoxi?
Here are the reasons why you must choose Edoxi for AI Training in Dubai.
- Project-Based Learning Throughout the Journey:
Each concept, ranging from foundational Python to advanced artificial intelligence, is reinforced through a series of mini-projects. This methodology ensures the practical mastery of machine learning models, data analysis, and neural networks. - Industry-Ready Portfolio Development:
Participants will create a comprehensive portfolio through hands-on exercises in data handling, predictive modelling, and artificial intelligence implementation utilising tools such as Jupyter Notebook, NumPy, and Pandas. - Progressive Learning Path:
Our structured curriculum comprises 18 modules, beginning with programming fundamentals and systematically progressing to advanced AI concepts. This design facilitates accessibility to complex topics via a learn-by-doing approach. - Focused Career Preparation:
Interactive coding sessions, coupled with analytical problem-solving exercises, effectively prepare participants for employment opportunities in the expanding AI sector in the United Arab Emirates. We place a strong emphasis on both technical proficiency and practical implementation skills.
Learning Support
- IDE Setup Assistance: Support is provided for setting up Google Colab and Jupyter Notebook.
- Version Control: Instruction on industry-standard Git practices is included.
- Study Resources: Comprehensive study materials are available for participants to take home.
- Post-Course Guidance: Participants will receive guidance for further study, career development, and application of learned skills.
Locations Where Edoxi Offers AI Course
Here is the list of other major locations where Edoxi offers the AI Course
Course Advisor
Tausifali Saiyed
Begin your AI journey at Edoxi under the expert guidance of Mr. Tausifali Saiyed, a technology professional with over 12 years of experience. He has trained more than 500 professionals and combines his extensive knowledge of Python and AI with practical applications in the classroom.
Mr. Saiyed holds an M.Sc. in Codmputer Science from the University of Greenwich and a Bachelor's in Computer Engineering from Sardar Patel University. His expertise covers full-stack development, Python application development, and various database technologies.
As a corporate trainer, he specialises in Python, AI, Machine Learning, and Deep Learning, having worked with organizations like Tech Mahindra and SBI. His background also includes teaching as an Assistant Lecturer at the University of Greenwich.
Join Mr. Saiyed to explore the dynamic world of technology and gain the skills to succeed!
Review & Ratings
FAQs
To join Edoxi’s Artificial Intelligence with Python course in Dubai, there are generally no strict prerequisites. The course is designed for both beginners and experienced professionals, making it accessible to anyone interested in learning about artificial intelligence and Python programming.
However, having a basic understanding of programming concepts can be helpful. No prior programming knowledge is required, allowing participants to start from the fundamentals and progress to more advanced topics. Having familiarity with working with data and a foundational understanding of mathematics can also enhance your learning experience, especially in areas like machine learning and data analysis.
Overall, anyone who is motivated to learn and interested in AI can benefit from this course.
The AI training courses at Edoxi span a total of 60 hours and are held at our Dubai location. We offer flexible scheduling from Monday to Thursday and Saturday, running from 11:00 AM to 8:00 PM, and on Sunday from 9:00 AM to 6:00 PM, with Friday as a day off. This setup is designed to cater to both in-person and online learners, making it ideal for those balancing work and study.
To become a Machine Learning Engineer or Data Scientist in Dubai, consider enrolling in our AI training course with Python designed to equip you for high-demand positions. You'll receive hands-on training in Python programming, data analysis, machine learning techniques, and AI applications. By the end of the course, you'll have a project portfolio that highlights your skills through real-world projects.
The career landscape for Artificial Intelligence in the UAE is quite broad, presenting a variety of opportunities across different sectors. Roles such as Data Analyst and Machine Learning Engineer are available for newcomers, offering attractive salaries and significant growth prospects in Dubai's thriving technology scene.
In the AI course, you'll explore a variety of important tools and technologies. You'll gain proficiency in Python, Jupyter Notebook, NumPy, Pandas, and well-known machine-learning libraries. The curriculum spans a wide range of topics, from data analysis to the implementation of deep learning techniques.
Edoxi does offer corporate AI training in Dubai. We provide tailored AI and Python training programs for companies, enabling teams to acquire hands-on skills that align with their business goals.
Upon successful completion of the course and assessment, you receive a professional certification from Edoxi, a KHDA-approved training institute in Dubai.
Absolutely! You can dive into Artificial Intelligence even if you don't have a computer science background. Our well-organised curriculum is designed for learners from all walks of life, guiding you step by step from the fundamentals of Python to more complex AI topics.
During the training, you'll engage in hands-on projects that involve data analysis, predictive modelling, machine learning applications, and neural networks, allowing you to create a well-rounded portfolio as you progress through the course.