AI and Machine Learning Bootcamp

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Go From Novice to Gen AI-ML Pro

Welcome to our AI-ML Mastery Bootcamp program, where an exhilarating learning journey awaits you! Get ready to become a confident AI-ML expert in under 5 months with our carefully designed curriculum. Immerse yourself in a whopping 92 hours of dynamic live instructor-led training, delivered by experts who transform complex concepts into engaging and understandable knowledge nuggets. 

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  • 92 Hours of Live Instructor-led Sessions 

  • 196 Hours of Top-Tier Self-Paced Videos 

  • 120 Guided Hands-On Exercises 

  • 191 MCQs to Gauge Your Progress  

  • 6 Comprehensive Assignments 

  • 15 Guided Video Projects 

  • 4 Real-World Capstone Projects

  • Weekly Doubt-Clearing Sessions with Experts 

  • 4 Complementary Courses Worth $2,000 

  • Career Support with Job Boost 360 

Embrace the Growing Demand for Generative AI-ML Experts

benefits of AI & Machine Learning Bootcamp

Organizations around the globe are leaving no stones unturned to harness the true potential of AI and Machine Learning in improving the quality of their services, streamlining company operations, and more. The demand for skilled AI professionals is growing at a rapid pace. As per the U.S. Bureau of Labor Statistics, the estimated job growth rate for AI Engineers is 22% from 2020-2030. Leverage the immense demand for AI experts, surf the wave of AI and Machine Learning, to elevate your tech career to new heights.

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Ready to unlock a high-growth career path in AI/ML?

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The KnowledgeHut Advantage

The most effective project-based immersive learning experience

Immersive Learning

  • On-demand videos
  • Guided hands-on exercises
  • Auto-graded assessments and recall quizzes
  • Assignments and projects

Learn by Doing

  • Learn to code. By actually coding.
  • Get project-ready with work-like experiences.
  • Learn on the job, like devs in tech companies.

Cloud Labs

  • Access fully provisioned dev environment.
  • Virtual machine spinned up in minutes.
  • Write code right in your browser.


  • Get advanced learner insights.
  • Measure and track skills progress.
  • Identify areas to improve in.

Blended Learning

  • On-demand, self-paced learning anytime.
  • Code review sessions by experts.
  • Access to discussion forums, community groups.

Your Certificate from Golden Gate University!

As you successfully complete the AI and Machine Learning Bootcamp, there's an extra feather in your cap: a certificate from the prestigious Golden Gate University, California (applicable for Blended Learning only). This distinct recognition not only celebrates your dedication but also the practical coding expertise you've honed in real-time.

path to AI & Machine Learning Bootcamp
prerequisites for AI & Machine Learning Bootcamp


  • Basic understanding of Python, including variables, loops, functions, and data structures
  • Good logical thinking and problem-solving skills
  • High-school level proficiency in Mathematics
  • Got the curiosity and passionate to learn about the latest in AI and ML? We’ll take care of the rest!

Who Should Attend

Software Engineers

Data Analysts

IT Professionals

Tech Enthusiasts


AI-ML Researchers

What You Will Learn

Python Programming

Ace Python concepts, including functions, modules, and error handling. Perform file input/output operations in Python. 

Machine Learning Basics

Understand the basics of machine learning, including supervised, unsupervised, and reinforcement learning. 

Mathematics for Machine Learning

Understand the concepts of functions, limits, continuity, derivatives, integrals, and optimization in calculus. 

Deep Learning

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

Neural Networks

Get the basics of Neural Networks right, and learn about Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). 

Generative AI

Understand generative AI and reinforcement learning, including generative adversarial networks and variational autoencoders.

Skills You’ll Gain

Python programming

Statistical modeling

ML algorithms

Deep Learning

Natural Language Processing (NLP)

Descriptive and inferential analysis

Data analysis and visualization

Data pre-processing techniques

Handling missing values

Transform Your Workforce

Get Future-Ready with a Skilled AI Team

Train your teams to master AI concepts and ace advanced Machine Learning technologies to drive profitability and build scalable solutions. Gain competitive edge, reduce time-to-market, and achieve important business objectives.

  • Enterprise-Wide Training
  • Small Team Training
  • Tech Team Training
  • Tech Leadership Development

500+ Clients

AI and Machine Learning Bootcamp Curriculum

Learning Objectives: Master Python concepts, data types, conditional statements, and user-defined functions. Learn how to perform file input/output operations in Python, and utilize NumPy and Pandas for data manipulation.

  • Python Programming
  • Input/Output Operations
  • NumPy and Pandas
  • Data Cleaning Techniques
  • Data Visualization Using Matplotlib and Seaborn

Learning Objectives: Understand essential mathematical concepts such as calculus, linear algebra, probability theory, and regression analysis for Machine Learning applications.

  • Calculus
  • Linear Algebra
  • Probability Theory and Statistical Measures
  • Probability Distributions and Sampling
  • Hypothesis Testing and Regression Analysis

Learning Objectives: Learn about supervised, unsupervised, and reinforcement learning, and build regression and classification models.

  • Supervised, Unsupervised, and Reinforcement Learning
  • Regression and Classification in Supervised Learning
  • Clustering and Dimensionality Reduction in Unsupervised Learning

Learning Objectives: Grasp the fundamentals of neural networks, work with TensorFlow and PyTorch, and explore Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

  • Basics of Neural Networks
  • TensorFlow and PyTorch.
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)
  • Long Short-Term Memory Networks (LSTMs)

Learning Objectives: Explore advanced topics like Natural Language Processing (NLP), generative AI, and reinforcement learning, including the use of Transformer models and Generative Adversarial Networks (GANs).

  • Natural Language Processing
  • Generative AI and Reinforcement Learning
  • Generative Adversarial Networks and Variational Autoencoders
  • Q-Learning and Policy Learning

1. Artificial Intelligence with Python Cookbook 

Set up your Python environment, explore data, implement heuristic search techniques, genetic algorithms, probabilistic models, and reinforcement learning. Delve into deep learning for text, images, video, and audio, while gaining essential problem-solving tools. Master AI and machine learning algorithms, testing, and deploying for production. 

  • Mode of Training: eBook 
  • Pages: 468  
  • Author: Ben Auffarth, Full-Stack Data Scientist | 15+ Years of Experience. 

2. ChatGPT 101 - Supercharge Your Work and Life with ChatGPT 

This course introduces ChatGPT and LLMs, offering tips for success and maximizing its potential. Discover its strengths, limitations, and verification importance. Create a Notion Swipe File, master prompt engineering, context primers, and tailor outputs for diverse applications, from social media content creation to professional efficiency. 

  • Mode of Training: On-demand videos 
  • Duration: 3 hours and 13 minutes 
  • Author: Sean Melis, multimodal designer with 15 years of experience. 

3. Python Natural Language Processing Cookbook 

Beginning with an NLP overview, this book offers recipes for text preparation, grammatical info extraction, semantic representation, and text classification. Explore topic modeling, chatbot development, and text data visualization, equipping you with a powerful toolkit for text processing. 

  • Mode of Training: eBook 
  • Pages: 284 
  • Author: Zhenya Anti, a Natural Language Processing (NLP) professional working at Practical Linguistics Inc.  

4. Deep Learning - Computer Vision for Beginners Using PyTorch 

This course offers a step-by-step approach, starting with PyTorch fundamentals and GPU utilization. Learn about PyTorch's AutoGrad, creating deep learning models, and working with CNNs using real-world datasets. Build a hangman game in Python and develop the skills to perform Computer Vision tasks with deep learning. 

  • Mode of Training: On-demand videos 
  • Duration: 7 hours and 14 minutes  

Frequently Asked Questions

AI and ML Bootcamp

By completing our AI and Machine Learning Bootcamp, you'll equip yourself with a comprehensive set of skills needed to excel in the world of AI engineering:

  • Gain expertise in Python programming, the foundation of AI and ML, to build powerful applications and algorithms.
  • Learn to build and implement regression, classification, and clustering models for data analysis and decision-making.
  • Dive into the world of neural networks, TensorFlow, and PyTorch to create advanced deep learning models like CNNs and RNNs.Unlock the potential of NLP, mastering text processing, sentiment analysis, and transformer models.
  • Understand the concepts of reinforcement learning, applying Q-learning and policy learning in real-world scenarios.
  • Master data manipulation with NumPy and Pandas and create insightful visualizations using Matplotlib and Seaborn.
  • Apply your skills to a series of hands-on projects, building a portfolio that showcases your capabilities to potential employers.
  • Cultivate teamwork and agile methodologies to contribute effectively to AI projects, while refining your communication skills for interviews.

By the end of the Bootcamp, you'll be job-ready, prepared to tackle AI and ML challenges, and armed with a standout portfolio that sets you apart as a sought-after AI Engineer.

To enroll for this AI and Machine Learning Bootcamp, participants should have:

  • Python: Since Python is widely used in AI and ML, the participants should have a basic understanding of Python, including variables, loops, functions, and data structures.
  • Problem-solving skills: Participants should have good logical thinking and problem-solving skills. This is essential for understanding the algorithms used in AI and ML.
  • Basic Mathematics: Although the course will cover the necessary mathematics, participants should have at least high school level knowledge of math.
  • Interest in AI/ML: Last but not least, participants should have a keen interest in AI and ML. These subjects can be quite complex and require a high level of commitment and self-study.
  • Time Commitment: This bootcamp requires significant time commitment. Participants should be able to dedicate time for self-study, assignments, and projects in addition to the class hours.

Throughout our online AI and Machine Learning bootcamp, you will be introduced to all the tools and skills that you will need to become proficient in AI and ML. This includes (but isn’t limited to): 

Python: The most popular programming language in the AI and ML community 

NumPy and Pandas: Libraries that are essential for data manipulation, data analysis, and numerical computations. 

TensorFlow and PyTorch: Powerful deep learning frameworks that enable you to build and train complex neural networks for various AI tasks. 

Keras: A user-friendly deep learning API built on top of TensorFlow and capable of rapid prototyping and experimentation. 

Matplotlib and Seaborn: Data visualization tools that allow you to create insightful and visually appealing plots and charts. 

Chat-GPT: An advanced AI language model developed by OpenAI, which utilizes deep learning techniques to generate human-like text responses based on input prompts. 

 No. To get the best out of this course, we recommend that learners have a basic understanding of Python, including variables, loops, functions, and data structures. 

The primary responsibility of an Artificial Intelligence Engineer is to design and develop intelligent algorithms that possess human-like reasoning abilities. These engineers harness the power of AI to create cutting-edge solutions that can tackle complex problems and make informed decisions, revolutionizing various industries with their innovative applications.

Career Benefits

In our fast-paced tech-driven world, the significance of Artificial Intelligence is paramount. With the ability to process various types of data, AI plays a crucial role in driving innovation and progress. By emulating human consciousness, machines can analyse information swiftly and efficiently, automating tasks across various industries. This remarkable advancement opens doors to unparalleled possibilities and propels us forward in remarkable ways. 

The future of computing revolves around AI, and it's experiencing an unprecedented surge. As an Artificial Intelligence Engineer in this early stage of AI's evolution, you'll have a unique opportunity to shape the future and make a significant impact on the computing world. Embracing this cutting-edge field will not only supercharge your career but also contribute to groundbreaking advancements that will shape how we interact with technology in the years to come. Don't miss out on the chance to be a trailblazer in the AI revolution and unlock a world of possibilities for your professional journey and the future of computing itself. 

Absolutely! The future is already here, and it revolves around AI. The field of AI Engineering is poised for an exponential surge in demand in the upcoming years, making it the perfect time to embark on this exciting journey. According to the US Bureau of Labor Statistics, AI jobs are projected to experience a remarkable 22% growth by 2030. Don't miss the opportunity to be at the forefront of this transformative technology and shape the world of tomorrow with your AI expertise! 

Bootcamp Experience

Our AI and ML Bootcamp is offered online with both live instructor-led sessions as well as on-demand self-paced mode. 

Our bootcamp instructors are distinguished AI experts who have spearheaded the AI revolution across various industries, armed with years of invaluable experience. Their expertise and guidance will empower you to harness the full potential of AI and Machine Learning, providing you with unparalleled insights and knowledge to thrive in this dynamic field.  

In an online classroom, students can log in at the scheduled time to a live learning environment that is led by an instructor. You can interact, communicate, view, and discuss presentations, and engage with learning resources while working in groups, all in an online setting. Our instructors for the course will ensure that you’re taken through the full course curriculum seamlessly, from foundational concepts to advanced techniques. 

Prepare for the AI and Machine Learning bootcamp with the following software and hardware requirements. Here's what you'll need:

Software Requirements: 

  • Python: As the primary programming language used in the course, Python 3.x should be installed. Python can be installed from the official website. 
  • Integrated Development Environment (IDE): An IDE such as PyCharm, Jupyter Notebook, or Visual Studio Code would be needed for writing and running Python code. 
  • Python Libraries: Various Python libraries will be used throughout the course, including NumPy, Pandas, Matplotlib, Seaborn, TensorFlow, and PyTorch. These can be installed using pip, Python's package installer. 
  • Git: Git might be required for version control and collaboration on projects. 

Hardware Requirements: 

  • Processor: A modern CPU (Intel i5 or equivalent / higher) would be sufficient for most of the tasks in this course. 
  • Memory: At least 8GB of RAM is recommended. For more complex machine learning models, especially in deep learning, more memory might be beneficial. 
  • Storage: A minimum of 20GB of free disk space is recommended for installing software, libraries, and datasets used in the course. 
  • Graphics Card: While not a strict requirement, a dedicated Graphics Processing Unit (GPU) can significantly speed up training times for certain machine learning and deep learning models. If you plan to work on complex deep learning models, a NVIDIA GPU with CUDA support is recommended. 
  • Internet Connection: A stable internet connection is required for downloading software, libraries, datasets, and for accessing course materials and online resources. 

In our AI and Machine Learning Bootcamp, we offer six immersive real-world assignments, providing you with hands-on experience in solving practical problems across various industries: 

Real Estate Analysis using NumPy: Dive into the world of real estate data, analyse housing prices, and calculate essential statistical metrics like mean, median, and standard deviation. 

Python Program for Banking and Finance: Develop a Python program tailored for a financial company, enabling you to read stock market data from CSV files and perform data analysis, generating valuable insights for decision-making. 

Hypothesis Testing in Healthcare: Work with a healthcare dataset to conduct hypothesis testing, evaluating the effectiveness of two different drugs for treating a specific medical condition, making data-driven medical decisions. 

Telecom Customer Churn Classification Model: For a telecom company, build a powerful classification model that predicts customer churn, using a provided dataset that includes customer information such as demographics, usage patterns, and customer satisfaction scores. 

Sentiment Analysis Model for Social Media: Develop a sentiment analysis model for ‘SocialBuzz’, to analyze customer opinions. Use a dataset consisting of customer reviews, tweets, or other social media posts. Preprocess the text data, apply techniques such as tokenization and text normalization, and train a sentiment analysis model using algorithms like Naive Bayes or recurrent neural networks (RNNs). 

Collaborative Filtering Recommendation System for E-Commerce: Build a recommendation system for ‘ShopGenius’, an e-commerce platform, using collaborative filtering. Utilize a dataset that contains customer purchase histories, item ratings, and user preferences. 

These real-world assignments will enrich your learning journey, allowing you to apply theoretical concepts to practical scenarios and build a standout portfolio that showcases your prowess in AI and Machine Learning.  

In this AI and Machine Learning Bootcamp, you will work on 15 step-by-step guided video projects. They are as follows: 

Project 1: Web Mapping with Python: Interactive Mapping of Population and Volcanoes 

Project 2: Building an English Thesaurus 

Project 3: Controlling the Webcam and Detecting Objects 

Project 4: Data Analysis and Visualization with Pandas and Matplotlib 

Project 5: Web Development with Flask - Build a Personal Website 

Project 6: GUI Apps and SQL: Build a Book Inventory Desktop GUI Database App 

Project 7: Mobile App Development: Build a Feel-Good App 

Project 8: Web Scraping - Scraping Properties for Sale from the Web 

Project 9: Build a Geography Web App with Flask and Pandas 

Project 10: Song Recommendation System Using t-Based Filtering 

Project 11: Movie Recommendation System Using Collaborative Filtering 

Project 12: COVID-19 Positive Cases Prediction Using Machine Learning Algorithm  

Project 13: Microsoft Corporation Stock Prediction Using RNNs  

Project 14: Birth Rate Forecasting Using RNNs with Advanced Data Analysis  

Project 15: Conversational Chatbot Development with Machine Learning