Artificial Intelligence Course Overview

Course Hours 60 hours
Batch Size 1 to 6
Accreditations AI CERT
Trainer Availability
Week Days: 11:00 AM - 8:00 PM
Weekends: 9:00 AM - 6:00 PM
Corporate Training Days 8 Days
Modes of Training
Classroom Training & Online Training
 

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 Course in Qatar

Edoxi offers a comprehensive 60-hour Artificial Intelligence course in Qatar with Python. It is suitable for beginners and experienced IT professionals and covers AI applications in various sectors, such as finance and healthcare.

The program has 18 modules and requires no prior programming experience. An expert in AI with over 12 years of Python programming experience teaches the classes. The lessons combine theory with hands-on coding and problem-solving.

Classes are held Monday to Thursday and Saturday from 11:00 AM to 8:00 PM, with Sunday sessions from 9:00 AM to 6:00 PM, allowing flexibility for working professionals and students. 

The course emphasises analytical thinking and communication skills essential for data science and AI success. Participants gain practical experience with tools like Jupyter Notebook, Pandas, and NumPy, preparing them for roles in leading AI companies.

Whether you're interested in automation or data-driven decision-making, our structured program will help you achieve your technical goals. Start your journey today!

Artificial Intelligence Course Features

  • Personalised Learning Options

    You can choose between personalised one-on-one sessions or small group training (4-6 students), ensuring focused attention and interactive learning.

  • Multiple Training Formats

    You can choose between in-person training at our Qatar facility or online sessions according to your preference.

  • 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.

  • Interactive Coding Environment

    You will have the chance to work in industry-standard development environments, ensuring you gain practical programming experience.

  • Comprehensive Study Materials

    You will have access to detailed presentations and PDF notes designed to support both in-class learning and self-study.

  • 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.

Artificial Intelligence Course Outcome

After completing Edoxi's AI training in Qatar, you will:

  • Develop a solid foundation in Python programming, essential for AI development.
  • Gain insight into fundamental AI principles, including machine learning, deep learning, and natural language processing.
  • Learn to apply AI techniques to real-world challenges.
  • Acquire skills in data manipulation and analysis using libraries like Pandas and NumPy, crucial for effective AI modelling.
  • Design, implement, and evaluate AI models using frameworks such as TensorFlow or PyTorch.
  • Enhance your critical thinking and problem-solving abilities, equipping you to address complex business challenges with AI solutions.
  • Be prepared for diverse roles in AI development, data analytics, and machine learning engineering, blending technical skills with industry knowledge.
  • Connect with industry professionals and peers, fostering valuable relationships in the AI and tech community.
  • Receive a competitive salary aligned with industry standards.

Average Monthly Salary for AI Developers in Qatar

Entry-level Job Designations Average Monthly Salary (in QAR)
Data Analyst 5,000 - 7,000
Associate ML Engineer 8,000 - 10,000
Associate Data Analytics Developer 3,000 - 26,000
Associate NLP Engineer 7,000 -11,000
AI Research Assistant 8,000 - 10,000
Machine Learning Specialist 15,000 - 25,000

*Note: These salary ranges are compiled through comprehensive research including professional salary websites ( Naukrigulf.com, Indeed.com, Glassdoor.com, Salaryexplorer.com) and insights from industry professionals in Qatar. 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 in Qatar

  • Systems Limited
  • Microsoft
  • MMH Technologies
  • Octopus Digital
  • Agile Tech
  • Amazon
  • Astrolab agency
  • Cisco
  • Dataline Technology Services
  • Ginger Technologies
  • IBM
  • MediaGuru

How To Get Certified in Edoxi’s AI Course?

Certification Image
1
Enquire & Enrol in Edoxi’s AI Training in Qatar
2
Attend the AI with Python Training
3
Complete the Post-Course Assessment
Certification Icon
Become an AI Certified Professional

Artificial Intelligence Training Options

Choose from the best training options that suit your needs

Classroom Instructor-led Training

  • Learn AI & Python at our facility 
  • Dedicated mentor guidance in small batches (4-6 learners) or one-on-one
  • Hands-on machine learning exercises with direct supervision
  • Real-time interaction for complex AI concepts
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Live Online Training

  • Same curriculum and mentorship quality from your location
  • Choose between small groups (4-6 learners) or one-on-one sessions
  • Live demonstrations of Python coding and ML algorithms
  • Flexible scheduling for working professionals
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Corporate Training

  • Customised Learning (Digital/ Instructor-led)
  • Flexible Pricing Options
  • Enterprise Dashboards for Individuals and Teams
  • Learner Assistance and After-support
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Why Choose Edoxi?

Here are the compelling reasons to select Edoxi for your AI training needs in Qatar.

  • Hands-On Project-Based Learning:  
    Every concept, from basic Python to sophisticated artificial intelligence, is solidified through a variety of mini-projects. This approach guarantees practical expertise in machine learning models, data analysis, and neural networks.
  • Comprehensive Portfolio Development: 
    Participants will build an extensive portfolio through practical exercises in data manipulation, predictive modelling, and AI implementation, utilising tools like Jupyter Notebook, NumPy, and Pandas.
  • Structured Learning Pathway:
    Our well-organized curriculum consists of 18 modules, starting with programming basics and gradually advancing to complex AI topics. This structure allows for easier comprehension of intricate subjects through a hands-on learning methodology.
  • Targeted Career Readiness:  
    Engaging coding sessions, along with analytical problem-solving tasks, effectively equip participants for job opportunities in the growing AI industry in the United Arab Emirates. We prioritise both technical skills and practical application.

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.

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

Edoxi has a Trustpilot Score of 4.5
4.5
Edoxi received a Score of 4.5 on Edarabia
4.5
Edoxi got a 4.5 Score on Goodfirms.
4.5
Aggregate Review Score
4.9/5

FAQs

What are the prerequisites to join Edoxi’s Artificial Intelligence with Python course in Qatar?

To join Edoxi’s Artificial Intelligence with Python course in Qatar, you typically don’t need any specific prerequisites. The course accommodates both beginners and experienced professionals, making it accessible to anyone interested in artificial intelligence and Python programming.

While prior programming knowledge is not required, having a basic understanding of programming concepts can be beneficial. The course starts from the fundamentals, allowing participants to progress to more advanced topics. Familiarity with data handling and a foundational understanding of mathematics can also enhance your learning experience, particularly in areas like machine learning and data analysis. 

Ultimately, anyone motivated to learn and interested in AI can benefit from this course.

What is the duration and schedule of AI training courses at Edoxi Qatar?

The AI training courses at Edoxi span a total of 60 hours and are held at our Qatar location. If you want to customise the course and duration, please contact our course advisors at +974 6687 3399. 

What is the scope of Artificial Intelligence careers in Qatar?

The scope of Artificial Intelligence (AI) careers in Qatar is expanding rapidly, driven by the country's push toward diversifying its economy and enhancing its technological landscape. AI careers in Qatar look promising, with considerable growth potential driven by government support, industry demand, and educational development. Those looking to pursue a career in this field can expect a dynamic and rewarding environment.

What tools and technologies are included in the AI course in Qatar?

The AI course in Qatar covers a range of essential tools and technologies, including Python, Jupyter Notebook, NumPy, Pandas, and popular machine learning libraries. The curriculum encompasses various topics, from data analysis to deep learning implementation.

Does Edoxi offer corporate AI training in Qatar?

Yes, Edoxi provides corporate AI training in Qatar. We offer customised AI and Python training programs for companies, helping teams develop practical skills that align with their business objectives.

Can I learn Artificial Intelligence without a computer science background?

Definitely! You can start learning Artificial Intelligence without a computer science background. Our structured curriculum is tailored for learners of all levels, guiding you from the basics of Python to more advanced AI concepts.

What types of AI projects will I work on during the training in Qatar?

 

 

Throughout the training, you'll work on hands-on projects that include data analysis, predictive modelling, machine learning applications, and neural networks, helping you build a comprehensive portfolio as you advance in the course.