Artificial Intelligence and Machine Learning Course

Artificial Intelligence (AI) is a broad field of computer science that involves developing intelligent machines that can perform tasks that traditionally require human expertise. The Artificial Intelligence Expert course introduces professionals to the fundamental and core concepts of AI.

ELIGIBILITY: This AI course is ideal for anyone planning to pursue a career in the field of Artificial Intelligence (AI). It has no mandatory prerequisites for enrollment; however, basic knowledge in the Artificial Intelligence domain is recommended.

CAREER OPPORTUNITIES:

Market Trends: Artificial Intelligence is revolutionizing the innovative market and is taking over various industries. In 2020, the global market of Artificial Intelligence was valued at USD 62.35 billion and is projected to grow at a CAGR of 40.2% from 2021 to 2028. The demand for qualified AI professionals has already surpassed that of Data Scientists, and this trend is expected to continue for the foreseeable future.

Salary Trends: The AI job market is growing at an astounding rate, making it a very lucrative career path. The AI jobs are not just expansive but also offer attractive packages. As reported by the Economic Research Institute, the average salary of an Artificial Intelligence Engineer ranges between AED 229,355 and AED 406,447 annually while the median gross salary is estimated to be AED 325,600 per annum.

Demand and Opportunities: Artificial Intelligence is the fastest – growing field in the world because of the demand for smarter system programs. The Insights reveal that open AI jobs are expected to increase at a CAGR of 31.6% to reach a total of 1,928,658 in 2023. LinkedIn reported a 190% increase in the skills needed for AI – based jobs from 2015 to 2017, indicating the enormous rise in demand for expertise in AI.

COURSE OUTLINE:

Artificial Intelligence Foundation

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

Machine Learning Foundation

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

TensorFlow 2.X platform

• 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

• Core Learning Algorithms Introduction
• Regression with Tensorflow
• Classification with Tensorflow

Neural Networks

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

Implementing Deep Natural Network

• 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

Deep Computer Vision – Convolutional and Neural Network

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

Recurrent Neural Network

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

Natural Language Processing

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

Reinforcement Learning

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

Deep Reinforcement Learning

• Architectures Of Deep Q Learning
• Deep Q Learning
• Policy Gradient Methods

Actor – Critic Methods

• General Adversarial Network
• GAN Introduction
• Core Concepts Of GAN
• Building GAN Model With Tensorflow 2.X, GAN Applications

Deploying Deep Learning Methods in the Cloud

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

KEY TAKEAWAYS:

After completing the Artificial Intelligence Expert course, participants will be able to:

• Understand the foundational concepts of Artificial Intelligence (AI)
• Integrate Machine Learning and Artificial Intelligence into the business
• Utilize the basic concepts of AI when implementing solutions that involve problem – solving, logic, inference, perception, knowledge representation, and learning
• Possess expertise in AI language expert systems or data mining tools
• Implement the scientific method for Machine Learning models

ACCREDITATION:

Our Artificial Intelligence Expert course is accredited by ISO 9001: 2015 and the Knowledge and Human Development Authority (KHDA).

ALUMNI: Our academy graduates are successfully placed in some of the top – notch companies in Dubai like Jumeirah, Aramex, Airarabia, Damac, Emaar, etc. They are entrepreneurs, career changers, and lifelong learners.

WHY LEARNER’S POINT:

Being one of the top providers of Artificial Intelligence Expert courses, we have substantial experience and profound knowledge in the field.

Our Artificial Intelligence Expert course provides the following advantages:

• Our Artificial Intelligence Expert course is designed based on real – world scenarios, formulating and evaluating practical requirements
• Our courses strive to provide a reality check and insight into the requirements of a challenging role and how to fulfill it
• We also provide live interactive sessions and hands – on experience through assignments associated with the actual work environment
• To enhance the learning experience of our students we provide organized group sessions and integrated training modules
• Our discrete approach to career guidance enables our students to get successfully placed in renowned organizations