Artificial Intelligence Engineering Bootcamp

Start Building Powerful AI Models And Land a Lucrative Tech Job

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Become a Sought-After AI Engineer

Ever unlocked your phone using facial recognition or asked Alexa ‘what’s trending on Twitter’? As one of the fastest-growing and most transformational technologies of our time, having added over 3 million new jobs in the past few years, AI is steadily growing in importance across industries. Here's your chance to build the skills to land a lucrative tech job as an AI Engineer.

KnowledgeHut’s skill-based AI Engineer Bootcamp is a comprehensive guided self-paced program for AI enthusiasts looking to accelerate their careers in this exciting field. The course covers all aspects of Artificial Intelligence, starting with the fundamentals of Math and Statistics and basics of Python programming to solving complex problems using Deep Learning and ML Models (Supervised, Unsupervised and Reinforcement Learning).

Master core concepts of Natural Language Processing, Deep Learning, and Neural Networks to acquire next-gen tech skills with intensive hands-on practice from experts and get ready to crack the hottest AI jobs.

Bootcamp Highlights

  • 288 Hours of E-Learning Material

  • 130+ Guided Hands-on Exercises

  • 9 Capstone Projects for a Job-Ready Portfolio

  • 15 Real-World Case Studies

AI Professionals are in Huge Demand

benefits of AI Engineer Bootcamp

Organizations around the globe are leaving no stones unturned to harness the true potential of AI in improving the quality of their services, streamlining company operations, and more. The demand for skilled AI professionals is growing at a rapid pace. Leverage the immense demand for AI experts, surf the wave of AI technology, to elevate your tech career to new heights.

AI experts utilize cutting-edge technologies like Deep Learning and NLP and combine them with advanced statistical modelling to help businesses achieve their corporate goals more accurately and profitably. With KnowledgeHut’s in-depth AI Bootcamp certification, cover all facets of AI, from basics to hands-on practice. Equipped with the latest AI tools, you are bound to thrive in the AI ecosystem. Acquire in-demand skills and become job-ready within a few months.

Gain the skills to land a lucrative tech job as an AI Engineer

Contact Course Advisor

Pool of Stellar Course Creators and Instructors

Our industry-validated curriculum is designed with inputs from our Software Engineering Advisory Board comprised of industry veterans and renowned experts. The program is delivered by top instructors with several years of experience under their belt.

David Haertzen

Big Data Analytics Leader

Denis Rothman

AI Author, Speaker, and Instructor

Jeffrey Aven

Principal Consultant

Gopikrishnan R

Co-Founder and CTO

Beau - Carnes

Director of Technology, Education

Jignesh Kariya

Sr. Database Consultant

Peter Henstock

Machine Learning & AI Lead

Ashish Gulati

Python & Data Science Consultant

Shobhit Nigam

Program Director

Phillip Kinn

Senior Data Scientist

Emmanuel Segui

Asst. Director, Reporting and Programming

Rahul Tiwari

Data Scientist and Co-Founder

Mark Strefford

Machine Learning Lead

George Mount


Dr. Vishwakarma J.S.

Enterprise Architect, CTO

Jeremiah Lobo

Data Visualization Lead

Enes Bilgin

Staff Machine Learning Engineer

Harish Masand

Project Manager - Digital Enablement (Data and AI)

Mo Medwani

Sr. Data Scientist

Marie Stephen Leo

Director of Data Science - APAC

Anatoly Zelenin

Freelance Trainer, Author

Bradford Tuckfield

Data Science Instructor and Consultant

Malvik Vaghadia

Principal Consultant - Data and Analytics

Rashmi Banthia

Data Scientist

Avery Smith

Data Scientist

Prince Kumar

Data Scientist

Sudhanshu Saxena

Sr. Data Scientist and Data Science Trainer

Azib Hasan

Freelance Trainer

prerequisites for AI Engineer Bootcamp


  • There are no prerequisites for attending this bootcamp.  
  • You can learn AI Engineering even without prior technical experience.
  • Some exposure to Mathematics, Statistics, Python or SQL will be beneficial.

Who Should Attend the AI Engineer Bootcamp

Data Analytics Professionals

Data Engineering Professionals

Anyone working in the IT industry

Developers who want to transition to AI

Students interested in making a career in AI

IT professionals aspiring to enter Data Science and AI

Impress Recruiters With a Stellar Project Portfolio

Build professional projects like the top 1% of AI Engineers and create a solid, job-worthy portfolio worthy of Tier 1 companies. Build your skills, boost your confidence, and land a lucrative job as an AI Engineer. Here’s a glimpse of some of the projects you’ll build:

  • SleepyFace
    SleepyFace Auto and Vehicles

    An app that scans drivers' faces and their eyes to see if they're properly awake or not using AI technology.  

  • OneArmDistance
    OneArmDistance Social Distance Detector

    An app that detects if social distance is being properly followed between two users in real-time by monitoring movements.

  • PreFace
    PreFace Face Swap

    Create realistic face swaps in any video and also bring popular photos alive with your face.

  • Recco
    Recco Audio/Movie Streaming

    Create your own playlist of music and movies based through recommendations based on your interests.

  • TraffiControl
    TraffiControl Traffic Control

    Reduce the number of accidents and waiting time at traffic signals based on information received from nearby intersections.

What You Will Learn

Python Programming

Ace Python concepts, different data types, conditional statements, and user-defined functions in Python

Statistical Modelling

Gain a thorough understanding of maths and statistics foundation for Machine Learning and AI 

Machine Learning with Python

Learn about Regression and Classification algorithms and build Machine Learning models 

Deep Learning

Learn to use Keras and TensorFlow to solve complex problems with Deep Learning models 

Natural Language Processing

Understand advanced NLP concepts, learn to use NLTK, Natural Language Generation, and NLP apps 

AI with Transformers

Understand why AI Transformer models are so unique and build robust applications using them 

Skills You Will Gain

Perform Descriptive Analysis on the data

Apply Inferential Statistics to draw conclusions

Write user-defined functions in Python

Use OOPs concepts for writing Python code in a better way

Solve errors and inconsistencies using Python

Perform Exploratory Data Analysis and Visualization

Perform Data Pre-processing

Deal with missing values and outliers

Perform Feature Selection and Feature Engineering

Build Regression Models

Develop and Test Machine Learning models

Build and Evaluate Classification models

Video preview 1.

Learning Objectives:

  • Master Descriptive Statistics and Probability Theory 
  • Learn different probability distributions such as Normal, Binomial, Poisson and many more
  • Learn Inferential Statistics to draw better inferences from the data
  1. Probability
  2. Statistics
  3. Linear Algebra
  4. Calculus
Video preview 2.

Learning Objectives: 

  • Start with the basics of Python programming
  • Learn how to use existing functions and create user defined functions
  • Work on different Python packages such as Pandas andNumPy
  • Understand visualizations using Python
  1. Introduction to Python 
  2. Code and Data 
  3. Building Blocks 
  4. Strings 
  5. Data Structures 
  6. Flow Control 
  7. Functions 
  8. Modules 
  9. Files 
  10. NumPy 
  11. Pandas 
  12. Regular Expressions
  13. Visualization 
Video preview 3.

Learning Objectives:

  • Difference between Regression and Classification.
  • Different algorithms that are used for Regression will be learnt
  • Different classification algorithms will be discussed.
  • Feature selection and Feature Engineering will be covered
  • Evaluate Machine Learning models
  1. Introduction to Machine Learning 
  2. Python Basics 
  3. Data in Python
  4. Data Visualization
  5. Statistics
  6. Advanced Data Analytics
  7. Machine Learning Basics
  8. Feature Extraction
  9. Support Vector Machines and Regression
  10. Supervised Learning
  11. Unsupervised Learning
  12. Dimensionality Reduction
  13. Ensemble Machine Learning
  14. Association Rules and Recommender Systems

Learning Objectives:

  • Starts with the foundations of Neural Networks and Deep Learning
  • Learn to use Keras and TensorFlow frameworks
  • Convolutional Neural Networks will be covered
  • Learn Generative Adversarial Networks (GANs)
  1. Diving into Deep Learning
  2. Getting started with TensorFlow
  3. Convolutional Neural Networks
  4. Advanced CNNs
  5. Natural Language Processing
  6. Generative Adversarial Networks (GANs)
  7. AI in the Real World 
Video preview 5.

Learning Objectives:

  • Understand what NLP is and its applications
  • Learn Natural Language Generation
  • Learn to use NLTK
  • Applications of NLP
  1. Introduction to NLP
  2. Essentials of NLP 
  3. NLP Feature Extractions 
  4. NLP with TextBlob  
  5. NLP with spaCy 
  6. Text Classification 
  7. Text Summarization
  8. Attention Mechanism
  9. Topic Modelling 
  10. Sentiment Analysis  
  11. Chatbots 
Video preview 6.

Learning Objectives:

  • Learn basic to advanced level concepts in machine learning.
  • Gain hands-on practical knowledge in how to implement and deploy machine learning algorithms
  • Go through the Case Studies from different domains.
  1. Scoping Out Business Requirements
  2. ML Projects in Different Sectors
  3. ML for Explainability
  4. Modeling Pipelines
  5. Deployment of ML Models and ML Ops 
  6. Best Practices in Machine Learning Industry

Learning Objectives:

  • Three paradigms of Machine Learning will be discussed
  • Learn the Reinforcement Loop
  • Work on Gym environment
  • Trade-off between exploration and exploitation
  • Contextual Bandit problems
  1. Introduction to Reinforcement Learning 
  2. Single-Step RL: Multi-Armed Bandits 
  3. Multi-Step Reinforcement Learning 
  4. Approaches for Real-World Reinforcement Learning 

Learning Objectives:

  • Experiencing Billion-Parameter Transformers for NLP
  • Multimodal Neurons for Vision Transformers
  • Learn Economic AGI(E-AGI)
  1. The Paradigm Shift of Transformers
  2. Experiencing Billion-Parameter Transformers for NLP 
  3. Multimodal Neurons for Vision Transformers 
  4. Economic Artificial General Intelligence (E-AGI) 

Learning Objectives:

  • Learn to do Image Processing
  • Deep Learning components for Feed Forward Neural Networks
  • CNN and its applications
  • Learn Segmentation and Object Recognition
  1. Introduction to Image Processing  
  2. Classification  
  3. CNN  
  4. Improving CNN  
  5. Segmentation and Object Recognition

AI Engineer Bootcamp FAQs

Bootcamp FAQs

There are no prerequisites for attending this bootcamp. You can learn AI Engineering even without prior technical experience.

Some amount of exposure to Mathematics, Statistics, Python and/or SQL will be beneficial.

The minimum recommended system requirement for attending the AI Bootcamp online is to have a workstation or laptop with at least 8GB of RAM and an internet connection. 

For this bootcamp you will need a web browser such as Google Chrome, Microsoft Edge or Firefox. Apart from this you will also need an Anaconda setup, but it can be installed as a part of the program. 

KnowledgeHut's AI Engineer Bootcamp is powered by on-demand self-learning with Cloud Labs and hands-on-practice.

All of the bootcamp instructors are renowned AI experts with years of experience in leading the AI revolution across different industries.  

Even freshers with no prior coding experience can enroll for our courses and become job-ready within just a few weeks.  

Workshop Experience

Currently our AI Engineer Bootcamp is offered online as an intensive self-learning mode with practice sessions on Cloud Labs.

You will need a workstation or laptop with Internet access, with at least 8GB of RAM.

Apart from that you will also need a web browser such as Google Chrome, Microsoft Edge or Firefox and Anaconda setup is preferred but this can be installed as a part of the program.

Additional FAQs on AI Engineer Bootcamp

All You Need To Know

Artificial Intelligence broadly refers to the introduction of human-like behavior in computers. That is, the replication of human consciousness within machines.  

The tech driven world we live in is undergoing a rapid change at an astonishing rate. The need for machines which can quantify not just logical data, but data of all kinds is at an all-time high. The mimicking of human consciousness within machines lets computers analyze data faster and automate several tasks, leading to giant strides in all kinds of fields.  

Even though a bit of prior knowledge of math, fundamental statistics, and programming will help you on your AI journey, there are no AI bootcamp eligibility requirements that must be met in order to enroll for our online Artificial Intelligence bootcamp. The AI bootcamp syllabus is designed such that you can go from zero AI skills to expert level skills as you learn.  

AI engineers are expected to have a strong foundation in programming languages such as C++, Python, R, Java etc. and a knack for analytics.  

The key role of an artificial intelligence engineer is to develop intelligent algorithms that are capable of reasoning like the human brain.  

There is no specific degree that you require to start your career in AI, having said that, a solid foundation in programming and logical reasoning will help you go a long way in your career. 

Enroll in one of the best Artificial Intelligence Bootcamps and learn all the skills you require to enter the vast field of Artificial Intelligence such as Python programming, Numpy, Pandas and much more. Learn their practical applications and gain hands-on experience in deploying these tools and technologies in real-world scenarios. You’re all set to become an AI Engineer!

Throughout our online artificial intelligence bootcamp you will be introduced to all the tools and skills that you will need in your AI journey which includes but is not limited to python programming, statistics modeling, machine learning, deep learning etc.  

AI is the future of computing, and it is going through a rapid growth. Being an Artificial Engineer in this early stage of AI would mean that you play a hand in how the future is shaped and it would do wonders for your career as well as the computing world itself.  

There are countless materials on the internet which can nudge you in the right direction in your AI journey. One of them being our Artificial Intelligence Engineer bootcamp which shall instill in you the skills and knowledge required to start your career in AI.  

As AI is an immensely vast field which includes various other fields of study within it, we strongly recommend that you conduct a deep dive into some of the allied fields such as machine learning, data science, statistics etc. to develop a deeper understanding of AI and what a career in AI would mean for you.  

The future is now, and it is intertwined with AI. AI Engineering shall see a drastic increase in demand in the coming years. Now would be an opportune time to jump on to the AI boat. The US Bureau of Labor Statistics predicts a 22% growth in AI jobs up to 2030. 

Artificial Intelligence is undergoing unprecedented growth and the demand for skilled Engineers is at an all-time high. The Harvard Business Review surveyed top corporations around the world and more than 75% of the management said they would rely upon Artificial Intelligence to help them make business decisions. Considering we interact with AI while using a number of popular mobile applications, AI has a strong presence in our daily lives and will need skilled AI Engineers to drive growth and development in the sector. 

In our Artificial Intelligence Engineer Bootcamp, you shall be made familiar with all the tools and skills that you require to jump start your career in AI. Some of said tools include Python, NumPy, Pandas, Keras, Tensorflow, SQL etc. 

One of the major challenges in AI is scarcity of clean and structured data. The amount of data required to induce human-like processing logic within an algorithm is immense and due to stringent data privacy rules in certain countries, there is a scarcity of easily available informative data.

The second major challenge in AI is as the field evolves at great pace, it lacks the right number of trained and skilled people to keep pace with the developments.  

Anyone with an eye for analytics and logical reasoning can achieve a prestigious career in AI. Even though there are no prerequisites that you must meet, a background in programming can take you a long way in your career. At the end of the day, the main thing to remember, is that programming tools, math, statistics are all skills that can be learnt. The will to learn and a good learning program is the key to success in this, as much as any other domain.  

If you are passionate about programming and analytics and you wish to play a hand in the future of technology, you should consider enrolling in one of the best Artificial Intelligence bootcamps.  

Some of the highest paying companies for Artificial Intelligence jobs are:

  • Amazon Inc 
  • Apple Inc 
  • Google  
  • Meta Platforms Inc 

If you are looking to get an edge over the competition in the field of AI, enrolling in an AI course or an online AI bootcamp shall give you extensive knowledge of the field, while showing companies that you are constantly looking to improve your skills and knowledge. 

The average salary of an AI engineer ranges from $92,938 to $150,183 per annum.  

After completion of our artificial intelligence bootcamp, you will be equipped to occupy various positions within AI. Some of these positions can include machine learning engineer, data scientist, business intelligence developer.  

Artificial intelligence is an immensely vast field. There are various roles that you will be able to occupy after the completion of our artificial intelligence bootcamp. Some of the prominent ones are Data Scientist, Deep Learning Engineer and Business Intelligence Developer. 

The roles & responsibilities of an AI engineer can include but is not limited to- coordination between Data Scientists and Business Analysts, testing and deploying models, converting machine learning models into APIs so that other applications can access them. 

Chase excellence and success will follow! The first step is to ensure that you are interested in the domain, read up about AI, its history and future prospects. If you’re really interested in AI, sign up for a course such as the Artificial Intelligence Bootcamp offered by KnowledgeHut, that combines theoretical concepts with practical exercises, helping you master the concepts you learn with hands-on projects. Get mentored by industry experts and get ready to jumpstart your AI career with our AI bootcamp online. 

The list of top companies to work in as an artificial intelligence engineer is a very long one. Some of them include:  

  • Google Inc 
  • Apple Inc 
  • IBM 
  • Facebook 

Our Artificial Intelligence Engineer Bootcamp is available at a cost of 1999 USD, available for a limited time at a discounted price of 1399 USD. Please check the Schedules section for the relevant AI bootcamp cost. 

AI is a vast subject which involves the use of multiple types of tools. Some of them are:

  • Numpy  
  • Python 
  • MongoDB 

Our Artificial Intelligence Bootcamp will equip you with all the skills and know-how that you will require to face any interview. Mentorship from experienced professionals, mock interviews, project reviews etc. are built into the program to ensure you are prepared to face any AI interview and land your dream job. 

What Learners Are Saying


Susie Daniels Data Engineer
This was a good learning experience, the course totally lived up to my expectations. Thanks to this course, I can now get my AI and ML career started.

Attended AI Engineer Bootcamp workshop in December

Kristina Nilsson Technical Lead
I really have to hand it over to the amazing instructors teaching the AI Engineer Bootcamp. They explained the entire curriculum so well even gave real-life incidents from their own experience. This helped us grasp concepts better.

Attended AI Engineer Bootcamp workshop in December

Oleg Babich Python Developer
I learnt all the important AI concepts and technologies thanks to this course. My instructor made sure all my doubts were cleared and explained everything in the simplest way. Completely happy with this program.

Attended AI Engineer Bootcamp workshop in December

Kevin Capaldi Senior Software Engineer
This AI Bootcamp is total value for money. I wasn't expecting the course curriculum to be so comprehensive. The learning approach was also fully hands-on with projects, assignments and exercises which helped a lot.

Attended AI Engineer Bootcamp workshop in December

Suresh Sharma Data Analytics Professional
This AI Engineer Bootcamp was a very good learning experience for me. I especially liked the Deep Learning and NLP modules. The instructors are very good, really know their material and clear all your doubts. Thank you, team KH!

Attended AI Engineer Bootcamp workshop in December