AI and Machine Learning 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.

 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.

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! 

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

Yes, installment options are available for payment of a fee for this AI and Machine Learning Bootcamp. To avail the installment option, please get in touch with us at support@knowledgehut.com. The team will explain how the instalments work and provide timelines for your case. Typically, the number of installments varies from 2 to 3, but the full amount must be paid before you complete the course. 

With our 100% Satisfaction Guarantee policy, you are assured of the highest standards of quality. At KnowledgeHut, we strive to ensure that your learning experience with us is beyond reproach. However, if for any reason your expectations are not met, we will refund the bootcamp cost in accordance with our 100% Satisfaction Guarantee policy. 

Yes, scholarships are available for students and veterans with grants that can vary up to 50% of the course fees to learn AI engineering. 

To avail scholarships, please get in touch with us at support@knowledgehut.com. The team shall send the forms and instructions to you. Based upon the responses and answers that we receive, our panel of experts takes a decision on the Grant. The entire process could take about 7 to 15 days. 

Yes, group discounts are available and apply to groups as small as three (3) participants. The more participants that attend a training course, the greater the discount. By registering in groups, you can typically save up to 20% to 30% on the course fee. For more details, please check out upcoming schedules.