Advanced Artificial Intelligence Course in Dubai

Thirteen in-depth modules covering advanced AI practices

Comprehensive 24-hour participative learning sessions

Explore AI applications in automation and industry innovations

Hands-on experience with AI development tools and frameworks

Work on real-world AI projects and case studies

Skilled instructors lead interactive live classes and Q&A sessions

Access training through flexible classroom or online options

4.8/5

6507 Enrolled

Overview

What you can expect to learn:

Explore deep learning and neural network architectures
Master machine learning algorithms and applications in AI
Learn AI-driven natural language processing (NLP)
Implement computer vision using deep learning models
Develop AI models for real-world problem-solving
Understand reinforcement learning and AI decision-making systems

Learning Objectives

Upon course completion, you will be proficient in:

Understand core concepts and algorithms of advanced AI

Master neural networks, deep learning and machine learning techniques

Demonstrate skills in developing applications in an AI language expert system shell or data mining tool

Develop proficiency in AI-based natural language processing (NLP)

Implement computer vision algorithms using deep learning frameworks effectively

Solve complex real-world problems with AI-driven solutions and models

Apply advanced AI techniques to innovate and enhance business processes

Ready to get started?

Prerequisites

To enrol for the Advanced Artificial Intelligence Course in Dubai, it is recommended:

Understanding of computer science fundamentals, programming languages (such as Python), data structures, algorithms, and mathematical concepts (such as linear algebra and calculus)
Experience with machine learning techniques, neural networks, and deep learning frameworks
A good grasp of statistics and probability may also be helpful

Overall ratings by our students

Upcoming sessions

Our Trainers

We, at Learners Point, take immense pride in our teaching methods and instructors. Our instructors are some of the best experts in their fields and employ a practical approach to learning. Many of them are globally recognised and have a diverse set of experience in their field of expertise. You are always sure to have the best in the industry as your teachers who are ready to guide you at every step and make the experience informative yet enjoyable. Apart from the focus on learning your chosen course, our instructors also encourage students to develop communication skills and interpersonal skills necessary to excel in the practical world.

Our cutting edge teaching methods make every program an immersive and productive experience for the learners. Our learning methods are research-driven and are continuously updated to stay relevant to present times as well as the future. You will enjoy practical applications of everything learned through theory and regular mock examinations to help monitor your progress. Our courses are led by an instructor in a classroom setup and we do offer online high-quality sessions as well for individuals. We also monitor the training sessions with a progress tracker to maintain high standards of instruction and ethics.

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

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.

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Curriculum

Understanding of computer science fundamentals, programming languages (such as Python), data structures, algorithms, and mathematical concepts (such as linear algebra and calculus).
Experience with machine learning techniques, neural networks, and deep learning frameworks.
A good grasp of statistics and probability may also be helpful.

Introduction to Artificial Intelligence (AI)
AI Data Strategy
AI Ethics, Issues and Concerns
AI Challenges
Use Cases, and Adaption

Data Science and ML Introduction
Mathematics for ML
Learning Methods
Popular ML Algorithms
Building Classification Models
Building Regression Models
Beyond Machine Learning

Tensorflow Introduction
Tensorflow Basic Concepts
Installation and Basic Operations In TF 2.X
TF 2.0 Eager Mode
Tensorflow 2.X - Keras

Core Learning Algorithms Introduction
Regression with Tensorflow
Classification with Tensorflow

Structure of Neural Networks
Neural Network - Core Concepts
Feed Forward Algorithm
Backpropagation
Building Neural Network from scratch using Numpy

Introduction to Neural Networks with Tf2.X
Simple Deep Learning Model in Keras (Tf2.X)
Building Neural Network
Model in Tf 2.0 for Mnist Dataset

Convolutional Neural Networks (CNNs) Introduction Cnnswith Keras
Transfer Learning In CNN, Style Transfer
Flowers Dataset With Tf2.X
Examining X-Ray With CNN Model

RNN Introduction
Sequences with RNNs
Long Short-Term
Memory Networks (LSTM RNNs) and Gru
Examples Of RNN Applications

Natural Language Processing Introduction
NLP With RNNs
Creating Model
Transformers and BERT
State of art NLP and Projects

Markov Decision Process
Fundamental Equations in RL
Model-Based Method
Dynamic Programming Model Free Methods

Architectures Of Deep Q Learning
Deep Q Learning
Policy Gradient Methods
Actor-Critic Methods

GAN Introduction
Core Concepts Of GAN
Building GAN Model With Tensorflow 2.X, GAN Applications

Amazon Web Services (AWS)
Deploying Deep Learning Models Using AWS Sagemaker

Frequently asked questions

Advanced Artificial Intelligence Course is a worldwide certification in advanced AI that provides individuals in Dubai with skills and concepts to develop AI applications. This course focuses on deep learning, natural language processing (NLP), computer vision, and AI deployment strategies. It benefits individuals who wish to advance their careers in AI and Machine learning. Some of these benefits are:

1. Expertise in advanced AI frameworks
2. Design AI solutions for complex challenges
3. Develop creative approaches to utilise AI
4. Open up opportunities in AI domain
5. Master advanced tools and AI-driven platforms

The UAE has increased its focus on the adoption of advanced technologies for the development of its society. With this initiative, UAE aims to be the world leader in AI by 2031 and expand the use of AI across sectors like education, energy, transportation, space, and technology, opening the doors to numerous opportunities in the country.

Today, Artificial Intelligence has conquered almost every industry. This course helps an individual interested in AI to remain relevant and gain expertise in this emerging technology, build a solid AI career and get the best artificial intelligence engineer positions in leading organizations.

The Advanced Artificial Intelligence Course is ideal to attend for individuals who are interested in AI and advance their careers ahead in this domain. Hence, this course is best for these individuals:

1. Professionals working in the domains of analytics, data science, e-commerce and search engine
2. Software professionals and new graduates seeking a career change

There are several eligibility criteria required by an individual before attending the Advanced Artificial Intelligence Course. They need to follow these sets of requirements thoroughly, as it is quite essential for the course. These prerequisites are:

Understanding of computer science fundamentals, programming languages (such as Python), data structures, algorithms, and mathematical concepts (such as linear algebra and calculus)
Experience with machine learning techniques, neural networks, and deep learning frameworks
A good grasp of statistics and probability may also be helpful

Several important topics related to AI and deep learning concepts will be covered in the Advanced Artificial Intelligence Course. The candidates will be taught by our instructors who will cover these topics thoroughly in 13 separate modules. Some of these topics are:

1. Introduction to Advanced AI Concepts
2. Deep Learning Architectures
3. Natural Language Processing (NLP)
4. Reinforcement Learning
5. AI in Robotics
6. Ethics and AI Governance
7. Generative Adversarial Networks
8. Advanced Machine Learning Techniques
9. Cloud-Based AI Platforms