AI Engineer
★★★★★ 5/5
Career Path program
Get ready to become an expert AI Engineer with this exciting learning opportunity! In this course, we will embark on a journey to the limitless possibilities of Artificial Intelligence. As technology continues to evolve, AI has emerged as a transformative force across industries.
New Session Starting:
1st of Dec 2023.
Program Duration:
4 months. 4-8 hrs/week.
Learning Format:
On-site Classes.
Course Overview
This course is designed to provide students with a comprehensive understanding of Artificial Intelligence and the necessary skills required to be an expert AI Engineer. With this course, you will advance your profession as an AI Engineer with skills including Data Science with Python, Machine Learning, Deep Learning, NLP, and Chat GPT. And so much more, so join now!
Key Elements:
- In-depth coverage of Artificial Intelligence and Machine Learning: Concepts and Principles.
- Practical exercises and real-world examples.
- Interactive discussions and peer collaboration.
- 4 modules and 1 final project.
- Hands-on experience with the latest technologies.
- Guidance from experienced instructors and industry experts.
- Comprehensive learning resources, including tutorials, case studies, and reference materials.
Relevant Courses
For further inquiry & details:
Learning Path
Fundamentals of Artificial Intelligence
Learners can unravel the mysteries around Artificial Intelligence and its business applications with the help of this module. An overview of machine learning, deep learning, performance measures, and AI ideas and procedures is provided in this Fundamentals of Artificial Intelligence module.
Applied Data Science using Python
You will receive a detailed introduction to Python’s data analytics tools and methods in this module. With the help of this module, you’ll enhance your Python skills, which are essential for many data science professions. You will learn Python for data science together with ideas such as data wrangling, mathematical computing, and more using a blended learning approach.
Understanding the Concepts of Machine Learning
With this Machine Learning module, you will be practicing Applied Learning and interactive laboratories, and you will learn about this fascinating area of artificial intelligence. It is necessary to grasp machine learning concepts to become an expert AI Engineer.
Deep Learning using Keras and TensorFlow
This Deep Learning using Keras and Tensorflow module is created by industry experts, and it is in line with the most recent best practices of the technology. Through this module, you will become an expert in deep learning theories and models utilising the Keras and TensorFlow frameworks.
Learning Path
Introduction to Full-Stack Development - MERN Stack
Getting started with full-stack development with the introduction of the course, and exploring course modules in detail.
Develop interactive Front-End with React
Learn all the basic and advanced concepts of front-end development including the major front-end development platforms like HTML, CSS, Javascript, and React.js Frameworks.
Fully functional Back-End with RESTFul and MongoDB
Learn all the basic and advanced concepts of back-end development including the major back-end development platforms like Node.js, Databases, RESTFul API and MongoDB.
Full-Stack Development - Merging Front-End and Back-End
Now, you will move towards the integration of the front-end and back-end and scaling them to make your website interactive and user-friendly.
Final Project - Development of an Advanced Chatbot for Personalised Customer Support using NLP and Transformer Models
The objective of this project is to design and build an advanced chatbot system that offers personalized customer support for a specific industry or domain. The chatbot will utilise state-of-the-art natural language processing techniques and transformer models to provide accurate and contextually relevant responses to user queries. You will create an intelligent chatbot that revolutionises customer support experiences in this challenging project and test your skills and abilities. The project aims to leverage the latest tools and technologies used by AI Engineers to develop an interactive chatbot solution that understands and responds to user queries with exceptional accuracy and natural language understanding.
AI Engineer Certification Advantages
To distinguish your profile as an AI Engineer, this thorough curriculum covers more than 8 software development tools and technologies.
With this programme, you will:
- Learn fundamental concepts of artificial intelligence and machine learning from recognised experts in the field, with information relevant to the industry.
- Implement the concepts of artificial intelligence and machine learning.
- Earn a course completion diploma that is recognised by the industry.
Skills Covered
-
Proficiency in
Machine Learning.
- Deep learning expertise.
- Natural Language Processing (NLP).
- Data analysis and visualisation.
- Programming and software development.
- Problem-solving and critical thinking.
- Model evaluation and performance metrics.
- Project management and presentation skills.
Tools Covered
Industry Trends
There is an abundance of demand for AI Engineers both now and in the future. Paysa estimates that there are less than 10,000 qualified individuals worldwide to perform these tasks, earning an average salary of £136K per year in the UK.
AI Engineer
Industry Growth
40% Annual Growth
For AI Engineer Jobs from 2020 to 2030
2 Million New Jobs
For the field of Cloud Architect jobs, there is a promising outlook from 2020 to 2030
AI Engineer
Annual Salary
Minimum
£70,870
Average
£110,420
Maximum
£136,478
Our Requirements
The AI Engineer course is designed for individuals who possess a strong interest in artificial intelligence and are eager to pursue a career in this rapidly evolving field. It is well-suited for aspiring software developers/engineers, data scientists/analysts, computer science graduates, professionals seeking a career transition, as well as researchers and academics in the field.
- Mathematics and Statistics.
- Data Analysis and Manipulation.
- Command Line Usage.
- Data Visualisation.
- Programming Skills.
