Artificial Intelligence Course
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Course Overview
Kickstart your career in Artificial Intelligence with this comprehensive AI Engineer Bootcamp, developed in collaboration with Simplilearn and IBM. This program offers a structured learning path covering Generative AI, ChatGPT, Machine Learning, Deep Learning, Natural Language Processing (NLP), and Reinforcement Learning, equipping you with the latest industry-relevant AI skills.
Through a blend of live-online classes, hands-on projects, and real-world capstone assignments, you'll gain expertise in key AI technologies, including TensorFlow, Keras, PyTorch, OpenAI’s ChatGPT, and DALL-E. Our bootcamp is designed to bridge the gap between theory and application, ensuring you develop practical AI solutions applicable across various industries.
With expert-led training, IBM industry masterclasses, hackathons, and career support services, this program provides the tools you need to thrive in AI and ML roles, whether you're transitioning into the field or enhancing your existing career.
What You Will Learn
By the end of this AI Engineer Bootcamp, you will be able to:
✅ Master Core AI and ML Concepts
- Gain expertise in Generative AI, prompt engineering, ChatGPT, and advanced AI models.
- Understand the purpose, scope, applications, and impact of artificial intelligence.
✅ Develop and Deploy AI Models
- Design and build intelligent agents for practical applications, including AI-driven decision-making models and games.
- Apply machine learning algorithms such as regression, classification, clustering, and recommendation systems.
- Work with supervised and unsupervised learning models to create AI solutions.
✅ Advance Your Programming & Data Science Skills
- Master Python programming essentials, including data types, operators, functions, and scripting.
- Perform data analysis and visualization using Pandas, NumPy, SciPy, Matplotlib, and Seaborn.
- Gain hands-on experience in data wrangling, hypothesis testing, and feature engineering.
✅ Explore Deep Learning & Neural Networks
- Learn to use TensorFlow, Keras, and PyTorch to build AI models.
- Develop deep learning models such as CNNs, RNNs, and GANs for computer vision, NLP, and speech processing.
- Understand transformer models and advanced AI architectures like GPT and BERT.
✅ Hands-on Industry Applications
- Work on real-world projects and case studies in healthcare, e-commerce, finance, and automation.
- Gain exposure to AI-powered automation, NLP-driven chatbots, and generative AI applications.
- Participate in IBM Masterclasses, hackathons, and hands-on AI labs for real-world skill-building.
With industry-recognised certifications from Simplilearn and IBM, this program sets you up for high-demand AI and ML roles in data science, automation, and artificial intelligence.
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Tools covered
The AI Engineer Bootcamp provides hands-on experience with industry-leading tools and frameworks, including:
AI & Machine Learning Frameworks
- TensorFlow – Build and train deep learning models efficiently
- Keras – Simplified deep learning API for neural network development
- PyTorch – Advanced deep learning framework for AI applications
Programming & Data Science Tools
- Python – Core programming language for AI and ML
- R – Statistical computing and data analysis
- Scala – High-performance programming for big data applications
- NumPy & SciPy – Mathematical and scientific computing libraries
- Pandas – Data manipulation and analysis
Big Data & AI Technologies
- Apache Spark – Distributed data processing for large-scale ML
- DALL-E & OpenAI – Generative AI for image synthesis and automation
- ChatGPT – AI-powered natural language processing and chatbot development
This version reflects the latest updates from Simplilearn’s course while maintaining clarity and relevance. Let me know if any further adjustments are needed.
Course Modules
Our Artificial Intelligence Engineer Bootcamp is a highly comprehensive and extensive course that upon completion, showcases your rich understanding and industry-related training in the artificial engineering world.
The applied knowledge and hands-on skills you will gain come from working on various simulations, real-world projects and case studies over 7 courses. The course content details for the bootcamp are summarised below.
This module provides a comprehensive introduction to Generative AI, covering its principles, applications, and challenges. You will learn about explainable AI, prompt engineering, and ChatGPT, gaining hands-on experience in designing and fine-tuning AI models for various use cases.
By the end of this module, you will be able to:
- Understand the fundamentals of Generative AI and its applications.
- Learn the importance of explainable AI and its role in AI decision-making.
- Apply prompt engineering techniques to optimise AI model performance.
- Explore ChatGPT’s capabilities, limitations, and real-world applications.
- Gain insights into the future of Generative AI and ethical considerations.
-Lesson 1: Course Introduction
This module covers the fundamentals of programming, including procedural and object-oriented programming (OOP). You will learn to set up Python and its IDE, use Jupyter Notebook, and apply key programming concepts like identifiers, indentation, and comments.
You will explore data types, operators, loops, and conditional statements, along with OOP principles such as methods, attributes, and access modifiers. The module also introduces multithreading, helping you write efficient programs. By the end, you will have a strong foundation in Python for AI and machine learning.
- Lesson 01: Course Introduction
- Lesson 02: Programming Basics
- Lesson 03: Introduction to Python Programming
- Lesson 04: Python Data Types and Operators
- Lesson 05: Conditional Statements and Loops
- Lesson 06: Python Functions
- Lesson 07: OOP Concepts with Python
- Lesson 08: Threading
This module introduces Python for Data Science, helping you develop the programming skills needed for AI and machine learning applications. Designed in collaboration with IBM, it covers essential Python concepts, data structures, and data manipulation techniques used in data science workflows.
You will learn to work with libraries like NumPy and Pandas, explore data wrangling, visualisation, and analysis, and gain hands-on experience with Jupyter Notebook for real-world data science applications.
-Lesson 1: Course Introduction
This module provides a comprehensive introduction to Python for data science, covering essential tools and techniques used in the field. You will develop key skills in data analysis, visualisation, and statistical modelling while applying Python to real-world scenarios.
Through a blended learning approach, you will gain hands-on experience with NumPy, Pandas, and data wrangling techniques, building a strong foundation for a career in data science.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Data Science
- Lesson 03: Essentials of Python Programming
- Lesson 04: NumPy
- Lesson 05: Linear Algebra
- Lesson 06: Statistics Fundamentals
- Lesson 07: Probability Distribution
- Lesson 08: Advanced Statistics
- Lesson 09: Pandas
- Lesson 10: Data Analysis
- Lesson 11: Data Wrangling
- Lesson 12: Data Visualisation
- Lesson 13: End-to-End Statistics Application with Python
Free Course:
-Math Refresher
Free Course:
-Statistics Essential for Data Science
his module provides a comprehensive introduction to machine learning, covering essential concepts, algorithms, and real-world applications. You will gain hands-on experience through interactive labs, practical exercises, and four hands-on projects, helping you build the skills required to become a successful machine learning engineer.
The course covers supervised and unsupervised learning, regression and classification models, ensemble methods, and recommender systems, equipping you with the knowledge needed to apply machine learning techniques in industry settings.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Machine Learning
- Lesson 03: Supervised Learning
- Lesson 04: Regression and Applications
- Lesson 05: Classification and Applications
- Lesson 06: Unsupervised Algorithms
- Lesson 07: Ensemble Learning
- Lesson 08: Recommender System
Free Course:
-Math Refresher
Free Course:
-Statistics Essential for Data Science
This module provides a comprehensive understanding of deep learning, distinguishing it from traditional machine learning. You will explore various neural network architectures, master forward and backward propagation, and learn essential deep learning optimisation techniques.
The course covers hyperparameter tuning, model interpretability, and performance enhancement, along with hands-on experience in CNNs, object detection, RNNs, and PyTorch. You will also learn advanced topics like transfer learning, transformer models for NLP, and autoencoders.
- Lesson 01: Course Introduction
- Lesson 02: Introduction to Deep Learning
- Lesson 03: Perceptron
- Lesson 04: Deep Neural Networks (DNN)
- Lesson 05: TensorFlow 2
- Lesson 06: Model Optimisation and Performance Improvement
- Lesson 07: Convolutional Neural Networks (CNN)
- Lesson 08: Transfer Learning
- Lesson 09: Object Detection
- Lesson 10: Recurrent Neural Networks (RNN)
- Lesson 11: Transformer Models for NLP
- Lesson 12: Getting Started with Autoencoders
- Lesson 13: PyTorch
The capstone project allows you to implement the skills you learned throughout this bootcamp. You will solve industry-specific challenges by leveraging various AI and ML techniques. The capstone project will help you showcase your expertise to employers.
Optional electives are available as part of this Artificial Iintelligence Engineering Bootcamp Program.
These are not mandatory to complete, but are available as additional courses to study if you are interested in expanding your knowledge and further implementing your skills.
- Elective 1 - Deep Learning with Keras and TensorFlow by IBM
- Elective 2 - ADL & Computer Vision
- Elective 3 - Natural Language Processing (NLP)
- Elective 4 - Reinforcement Learning
- Elective 5 - Advanced Generative AI
- Elective 6 - Industry Masterclass by IBM
Payment Options
Course projects
This artifical intelligence certification course delivered by Simplilearn is co-developed with IBM and includes real-life, branded projects in different industries.
These real-world projects are designed with impact to help you master the key concepts of artificial intelligence such as supervised and unsupervised learning, reinforcement learning, support vector machines, Deep Learning, TensorFlow, neural networks, convolutional neural networks, and recurrent neural networks.
Below are the details on projects you will be working on.
Project 1: Sales Analysis for Business Growth
Project 2: Growth Planning for a Retail Chain
Project 3: Employee Turnover Analytics
Project 4: Segmentation of Songs
Project 5: House Loan Data Analysis
Show off your achievements
Earn your Artificial Intelligence Engineer Bootcamp Certification
Digital certificates are the new way for Upskilled and Simplilearn graduates to offer proof of their hard earned knowledge or skill set.
You will receive individual certificates after each short course. Additionally, upon completion of the entire bootcamp, you will earn a certificate demonstrating your competence and expertise as a artificial intelligence engineer.
Differentiate Yourself
Set yourself apart from the competition with the Artificial Intelligence Engineer Bootcamp certificate. This is your ticket to get your foot through the door and proof that you have applied artificial intelligence engineering knowledge and skills to real-world projects making you job ready as a full-fledged expert.
Share your achievement
You worked for it, you earned it! Share your achievement loud and proud! Talk about your artificial intelligence engineering certification on LinkedIn, Twitter, Facebook. Add it to your CV to stand out and showcase to your employers.
Data Analyst Course course advisor
Ronald van Loon
Top 10 Big Data and Data Science Influencer, Director - Adversitement
Named by Onalytica as one of the three most influential people in Big Data, Ronald is also an author of a number of leading Big Data and Data Science websites, including Datafloq, Data Science Central, and The Guardian. He also regularly speaks at renowned events in IoT, Big Data and Data Science.
FAQs
An Online Bootcamp is an intensive and accelerated learning program made up of a collection of self-paced eLearning components and live online classes that students are required to attend.
The Online Bootcamp program curriculum contain a combination of specifically chosen courses and career-critical skills that are aligned to a job role.
A Short Course on the other hand are shorter courses that is designed to target developing a specific skillset or topic. They generally are much quicker to complete than Bootcamp Programs.
No qualification is necessary for a career in artificial intelligence. However, it is recommended that the student has a fundamental understanding of python programming and statistics.
Online education or distance learning has made education more accessible for students and professionals around the world. Online learning has also transformed the way individuals learn in terms of learning material and practice. An online artificial intelligence course syllabus is very much different to a traditional course syllabus. While there are in-person benefits such as collaboration in a traditional course, there is lack of flexibility as you must attend your classes in person and material is not readily available.
In an online artificial intelligence course, online learning material (written content, interactive quizzes, video content and hands-on exercises and real-world projects) is readily available with lifetime access, which you can access anytime anywhere. In an online course, there is higher flexibility as you get to work at an individualised pace, set your own study hours and time to suit your current lifestyle. Online learning courses are also designed with live interaction and practical projects, which allow you to build peer to peer collaboration and gain hands on experience in the artificial intelligence field.
There are numerous online artificial intelligence courses. Sometimes it can be overwhelming ito pick out the best option. Finding the right artificial intelligence course for you is not only important but will set you up for success in your career as a artificial intelligence professional.
It is best to take into consideration the below factors when choosing the best course for you:
- Quality of education
- Content material
- Credibility of courses
- Funding options
These days employers and organisations value a hands-on learning approach that covers working on real projects and applications, as well as experience working with cutting edge technologies. The best artificial intelligence course for beginners should involve practical content, thorough video content and include live interactions between advisors and students. Good artificial intelligence courses such as bootcamps are engaging, challenging and motivating for students to enjoy, whilst enhancing their knowledge and skills.
A related degree in Artificial Intelligence is not necessary to be eligible for an online AI learning course. Most online artificial intelligence programs are built on fundamental computer science fundamentals such as Python programming and statistics.
This AI online course is designed for both beginners and experienced professionals looking to enter the field.
Artificial Intelligence (AI) is the science and engineering of making intelligent machines, especially computer programs. It enables computer programs to perform tasks that usually require human intelligence. Using various principles and techniques in AI, computers can be trained to accomplish tasks by processing large volumes of data and recognizing patterns.
Artificial intelligence (AI) makes it possible for machines to learn for themselves, make decisions and perform human-like tasks. By harnessing the power of AI, we can develop systems that automatically understand their environment, detect changes and react accordingly. This unique ability disrupts traditional models of learning and decision-making, dramatically increasing speed, precision and efficiency.
As such, online AI learning courses are increasingly valued due to their emphasis on a hands-on focused and immersive learning approach. These days many organisations value skills that are job ready and demonstratable, and AI Certification bootcamp courses are an appraised path to achieve this practical experience.
The Artificial Intelligence online course is designed for both entry-level individuals and for experienced professionals looking to enter the world of artifical intelligence engineering.
You'll find a range of students from various backgrounds such as:
- Developers aspiring to be an AI Engineer or Machine Learning Engineer
- Analytics Managers who are leading a team of analysts
- Information Architects who want to gain expertise in Artificial Intelligence algorithms
- Analytics professionals who want to work in machine learning or artificial intelligence
- Graduates looking to build a career in Artificial Intelligence and machine learning
- Experienced professionals who would like to harness Artificial Intelligence in their fields to get more insight
To enrol in this Artificial Intelligence online course, you'll need to first submit an enquiry form via our website. You'll need to provide the following details:
- Your Name
- Best Phone Number
- Email Address
Once you've submitted your online form, one of our education consultants will be in touch within 48 hours.
During the consultation, you'll be able to ask questions regarding payment options, learning content and what career outcomes you can pursue if you complete your studies.
There are various career roles an AI certification student can work in upon completion of the online course. Some examples of career roles include: AI Engineer, AI Developer, AI Architects, Machine Learning Engineers, Data Scientists or Big Data Engineer