Invest in your future with our comprehensive, hands-on course in machine learning - designed to take you from beginner to expert, to stay relevant and ahead of the competition. A course by Arjun Jain.
The advancements in AI and machine learning are increasing exponentially. AI is revolutionizing the way we solve problems and make decisions. It has become increasingly important to upskill to the latest developments in the field, as more and more companies embrace AI.
AI Masterclass takes you from the fundamentals of machine learning to the state-of-the-art. You will be taught from scratch, with in-code examples provided by our experienced faculty. We collaborate with top industry experts and provide personalized guidance to learners.
AI Masterclass is a hands-on online learning platform that helps you learn better by applying what you learn in the course to real-life projects, reinforcing learning by doing.
With this platform, you can acquire the knowledge and skills necessary to open up new career opportunities and provide a competitive advantage to organizations.
AI Masterclass is taught by an experienced team led by industry leader and AI expert Arjun Jain.
Arjun Jain is the Founder and CEO of UAVIO Labs and Fast Code AI. He is an Adjunct Faculty at the CDS department at IISc, leading a deep learning research group. With a Ph.D. in Computer Science from the Max-Planck Institute for Informatics in Germany, Arjun has over 15 years of experience in AI and related fields.
The other core faculty members are carefully selected for their expertise in AI, Machine Learning and Data science and are committed to providing learners with the most current and relevant knowledge and skills.
AI Masterclass understands the need to stay agile and constantly upskill in today’s dynamic work environment. With its team of experienced and skilled faculty, it aims to be the trusted partner needed in this upskilling journey.
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Registrations for other courses will open shortly. Stay tuned!Subscribe
Currently registrations are open for AdvancedML1.
We have several upcoming courses in the pipeline, with the first one being an Advanced Machine Learning course taught in a semester style format (15 weeks). This course is not intended for beginners, and a minimum commitment of 10 hours per week (including 3 hours of instruction) is required to succeed. Prior experience with deep learning and proficiency in Python programming is also expected.
To ensure that the program is suitable for you, there will be a selection process where we will speak with each registered individual who completes the form.
Week #1: Tensor Operations, Back Propagation, Advanced Optimization Techniques
Week #2: SOTA ConvNet Backbones and Transfer Learning Techniques
Week #3: Working with Data Teams: Maximizing Data Efficiency with Voxel 51 and other Practical Tips
Week #4: Sequential Model Baselines: RNNs, GRUs, and LSTMs
Week #5: Techniques and Challenges of Real-Time Object Detection for Autonomous Cars
Week #6: Building Generative Adversarial Networks from Scratch
Week #7: Exploring Variational Auto Encoders: Theory and Hands-on Implementation
Week #8: From Attention to Transformers: An In-depth Exploration of BERT, GPT, Vision Transformers, and More
Week #9: Generating Images with Diffusion Models: Theory and Implementation
Week #10: Metric Learning, Image Embeddings, and Joint Image and Text Embeddings: A Deep Dive into CLIP, UniFORM, and Beyond
#1 Advanced NLP Models in Action: Building Real-World Applications with GPT-3, LLaMA, and ChatGPT
#2 Building Real-World Applications for Generative Image and Human Motion Generation
#3 Building Real-World Applications coninued
#4 Demystifying Recommendation Systems: Techniques and Applications
#7 Capstone Project Presentations by Participants.
Note: The capstone project is a critical component of this course, and we place a great emphasis on it. To ensure that each participant has the necessary resources, we will provide ample compute and GPU resources to explore and work on their capstone project. The first two modules of the course focus on learning new topics, while the final module focuses on applying what we have learned to build real-world applications. These applications will serve as inspiration for your own capstone project, and we encourage you to think creatively and push the boundaries of what you have learned throughout the course.