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Artificial Intelligence Training Course

Typing on keyboard with AI robot and digital interface – AI Online Training
Gain 60 hours of in-depth online AI training with Python at Edoxi. Our comprehensive course covers essential concepts and advanced machine learning techniques for both beginners and experienced IT professionals. Our AI with Python course features hands-on exercises with Jupyter Notebook, Pandas, and NumPy, preparing you for roles in top global AI companies. Launch your career in AI with Python, known for its extensibility, extensive libraries, and strong community support.
Course Hours
60 hours
Corporate Days
8-10 Days
Learners Enrolled
150+
Modules
18
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Course Rating
4.9
star-rating-4.9
Mode of Delivery
Online
Certification by

What You'll Learn From the Artificial Intelligence Course?

Python Programming Fundamentals
Edoxi will help you master Python basics. Understand data structures, object-oriented programming, and essential libraries like NumPy and Pandas for AI development.
Data Analysis and Visualization
You will learn to manipulate data using Pandas. Conduct exploratory data analysis. Create visualizations with Matplotlib for meaningful insights.
Machine Learning Foundations
You will gain practical experience with supervised learning (regression and classification). Explore unsupervised learning (clustering) algorithms using Python.
Natural Language Processing Basics
You will understand and implement NLP concepts using classical and deep learning approaches in Python.
Neural Network Implementation
You will learn the fundamentals of artificial neural networks and convolutional neural networks for AI applications.
Practical AI Project Development
You get to apply your skills through hands-on projects using Jupyter Notebook. Work with data formats like JSON, CSV, and Pickle in real-world scenarios.

 About the Artificial Intelligence with Python Course Online

Edoxi offers you a 60-hour online course in Artificial Intelligence with Python for beginners and seasoned IT professionals. This globally recognised program equips you with the skills to leverage AI technologies across diverse industries, including finance and healthcare.

Our well-structured AI with Python course curriculum spans 18 modules, ensuring no prior programming knowledge is required. Led by an expert trainer with over 12 years of industry experience, the Artificial Intelligence with Python Course perfectly balances theoretical insights and hands-on practice. You will engage in interactive coding and problem-solving exercises that enhance your learning experience.

At Edoxi, we focus on developing critical analytical thinking and communication skills essential for success in data science and AI careers. Our comprehensive study materials cover everything from foundational concepts to advanced techniques, preparing you for roles in leading AI companies worldwide. You will gain practical experience with tools like Jupyter Notebook, Pandas, and NumPy, and learn how to apply AI in automation and data-driven decision-making.

Whether you’re looking to advance your career or explore emerging technologies, our structured Artificial Intelligence with Python Course will transform your aspirations into practical expertise. 

Enroll today and take the first step towards a successful career in AI!

Artificial Intelligence Course Features

Personalised Learning Options

Choose between one-on-one sessions for individualised attention or small group training (4-6 students) for interactive learning.

Practical Project Portfolio

Engage in mini-projects focused on data handling, machine learning, and neural networks to create a portfolio demonstrating your skills.

Comprehensive Study Materials

Access detailed presentations and PDF notes that support both in-class learning and self-study efforts.

Multiple Training Formats

Based on your preferences and convenience, you can select training either in person at our facility or online.

Interactive Coding Environment

Gain hands-on experience using industry-standard development environments, enhancing your practical programming skills.

Professional Assessment & Certification

Receive a course completion certificate from Edoxi after successfully passing the post-course assessment, validating your expertise.

Who Can Join Our AI Course?

Fresh Graduates & STEM Professionals

Recent graduates in Computer Science, IT, Engineering, Mathematics, or any related discipline.

Software Developers & IT Professionals

Programming professionals seeking to expand their expertise into AI and machine learning.

Business & Analytics Professionals

Business analysts, data analysts, and professionals from finance or healthcare sectors.

Career Transitioners

Professionals from any background with analytical thinking abilities and basic familiarity with programming concepts.

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.

Artificial Intelligence 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 7.2.2: 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 13.1.1: Basics of Machine Learning
    • Lesson 13.1.2: Supervised and Unsupervised Learning
    • Lesson 13.1.3: Data Preparation and Preprocessing
  • Chapter 13.2: Data Processing

    • Lesson 13.1.1: Importance of data in AI
    • Lesson 13.1.2: Data cleaning and preprocessing techniques
    • Lesson 13.1.3: 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 15.2.2: Evaluating the 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

Download AI Course Brochure

Projects and Case Studies Involved in the Artificial Intelligence with Python Course

Edoxi's online Artificial Intelligence with Python Course will include the following projects and case studies;

Projects

  • Housing Price Prediction

    Develop a machine learning model in Python to forecast housing prices based on historical data. This project will enhance your understanding of data preprocessing, regression techniques, and the evaluation of machine learning models.

  • Customer Segmentation through Clustering

    Implement an unsupervised learning model using k-means clustering to segment customers. You will analyse real-world datasets to classify customers based on their purchasing behaviour.

  • Image Classification with Deep Learning

    Design a convolutional neural network (CNN) to categorize images. This project provides practical experience in deep learning, leveraging frameworks like TensorFlow and Keras.

Case Studies

  • Case Study

    AI-Driven Retail Demand Forecasting: A retail company utilised AI models developed by a course participant to effectively predict product demand. As a result, they achieved a 20% decrease in both overstock and understock situations, greatly enhancing their supply chain management.

Artificial Intelligence with Python Training Outcomes and Career Opportunities

Edoxi’s Artificial Intelligence with Python Course will help you develop a solid foundation in Python programming and fundamental AI principles, including machine learning, deep learning, and natural language processing. Upon completing Edoxi's AI training, you will:

Course Outcome Image
Apply AI techniques to solve real-world problems effectively.
Analyse and manipulate data using essential libraries like Pandas and NumPy, vital for successful AI modelling.
Design, implement, and assess AI models with popular frameworks such as TensorFlow and PyTorch.
Enhance your critical thinking and problem-solving skills to address complex business challenges using AI solutions.
Prepare for careers in AI development, data analytics, and machine learning engineering, combining technical expertise with industry insights.
Expect a salary that aligns with industry standards.

Job Roles After Completing AI with Python Training

  • Data Analyst
  • Associate ML Engineer
  • Associate Data Analytics Developer
  • Associate NLP Engineer
  • AI Research Assistant
  • Junior Python Developer
  • Machine Learning Specialist

AI Training Options

Live Online Training

  • 60-hour online AI with Python 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

Corporate Training

  • 8-10 days of comprehensive Corporate Training

  • Customised Learning (Digital/ Instructor-led)

  • Flexible Pricing Options

  • Enterprise Dashboards for Individuals and Teams

  • Learner Assistance and After-Support

  • Training can be delivered at a star hotel, at the client’s premises, or at Edoxi.

Do you want to customise this course for Corporate Training?

Talk with our course advisors for course customisation.

How To Get Certified in Edoxi’s AI Course?

Here’s a four-step guide to becoming a certified AI professional

Do you want to be a Certified Professional in AI with Python?

Join Edoxi’s Artificial Intelligence Course

Why Choose Edoxi for AI Course?

Here are the compelling reasons to select Edoxi for your AI Training.

Hands-On Project Learning

Every concept, from basic Python to sophisticated artificial intelligence, is solidified through a variety of mini-projects. This approach guarantees a practical understanding of machine learning models, data analysis, and neural networks.

Portfolio Development for Industry Readiness

Participants will build an extensive portfolio through practical exercises in data management, predictive modelling, and AI implementation using tools like Jupyter Notebook, NumPy, and Pandas.

Structured Learning Pathway

Our well-organised curriculum consists of 18 modules, starting with programming basics and gradually advancing to complex AI topics. This structure makes intricate subjects more accessible through a hands-on learning experience.

Targeted Career Preparation

Engaging coding sessions, along with analytical problem-solving tasks, effectively equip participants for job opportunities in the growing AI industry worldwide. We prioritise both technical skills and practical application.

Personalized IDE Setup Assistance

Receive step-by-step guidance for configuring both Google Colab and Jupyter Notebook, ensuring a seamless start to your coding journey regardless of your device or prior experience.

Industry-Standard Version Control Training

Learn best practices in Git, the leading version control system, including hands-on exercises for tracking changes, collaborating on projects, and managing code efficiently.

Comprehensive Study Materials

Get access to a curated collection of detailed study resources, including practical coding exercises and real-world project examples.

Ongoing Post-Course Guidance

Benefit from tailored advice on further education opportunities, career pathways, and strategies for applying your new skills in professional and personal projects, ensuring continued growth beyond the classroom

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Edoxi is Recommended by 95% of our Students

Meet Our Mentor

Our mentors are leaders and experts in their fields. They can challenge and guide you on your road to success!

mentor-image

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.

Locations Where Edoxi Offers AI Course

Here is the list of other major locations where Edoxi offers AI Course

FAQ

What are the prerequisites to join Edoxi’s Artificial Intelligence with Python course?
To join Edoxi’s Artificial Intelligence with Python course, 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. 
What is the duration and schedule of AI training courses at Edoxi?
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.
What kind of AI projects will I work on during the training?
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.
Can I learn Artificial Intelligence without a computer science background?
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.
Which tools and technologies are covered in the AI course?
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.