Prepare yourself for real success.
AI Engineering
Career Track
AI Engineering
Career Track
The AI Engineer career track offers a curated list of required and optional courses and workshops that guide you from beginner to advanced, empowering your journey to become an AI professional through hands-on learning
15 Courses
65 Hours
4 Months
Know
Roles & Responsibilities
Designed for college students who want real-time learning from AI professionals.
This program is designed for college students aspiring to become AI engineers
DATA COLLECTION & pREPARATION
Collecting data from sources such as web scraping and enterprise databases, ensuring the information is clean and relevant for artificial intelligence projects. After acquiring the data, the engineer applies feature engineering, stores data in appropriate systems like vector databases, and structures it for efficient retrieval and model training
MODEL Development
Design and refine model architectures such as deep learning neural networks, leveraging pre-trained models and transfer learning to accelerate development and optimize performance. Throughout model development, they employ ML evaluation metrics, perform hyperparameter tuning, and implement advanced strategies like RAG (vector search combined with LLMs) to improve accuracy and efficiency.
DEPLOY AI MODELS
Package models and export trained weights for serving through cloud platforms, ensuring reliable and scalable access. By leveraging containerization with Docker and automating through CI/CD pipelines, they integrate MLOps principles, monitor model drift, and uphold ethics by addressing bias and data privacy in production environments
DATA COLLECTION & pREPARATION
Collecting data from sources such as web scraping and enterprise databases, ensuring the information is clean and relevant for artificial intelligence projects. After acquiring the data, the engineer applies feature engineering, stores data in appropriate systems like vector databases, and structures it for efficient retrieval and model training
MODEL Development
Design and refine model architectures such as deep learning neural networks, leveraging pre-trained models and transfer learning to accelerate development and optimize performance. Throughout model development, they employ ML evaluation metrics, perform hyperparameter tuning, and implement advanced strategies like RAG (vector search combined with LLMs) to improve accuracy and efficiency
DEPLOY AI MODELS
Package models and export trained weights for serving through cloud platforms, ensuring reliable and scalable access. By leveraging containerization with Docker and automating through CI/CD pipelines, they integrate MLOps principles, monitor model drift, and uphold ethics by addressing bias and data privacy in production environments
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Courses
Introduction to Artificial intelligence (OPTIONAL)
This course introduces the foundations of artificial intelligence, its core technologies, industry context, and career pathways. Upon completion, learners will have the essential understanding necessary to confidently plan and pursue a career in AI.
Duration : 2 Days
LEARN PYTHON FUNDAMENTALS
This course covers essential Python programming skills, project building using APIs, and robust error handling techniques while introducing data manipulation with popular libraries, web scraping, and workflow automation tasks
Duration : 20 Hours
ADVANCE Your PYTHON Learning
This course provides a strong foundation in Python for AI, covering data handling, visualization, and hands-on projects with LLMs and app development. Learners also gain experience with the full AI/ML cycle, pretrained models, neural networks, and building AI-driven web applications.
Duration : 20 Hours
AI MODEL DEPLOYMENT
This course teaches you how to take your trained AI models and make them available for use in real-world applications. You’ll learn the steps needed to put models into production, from packaging and exporting to deploying on cloud platforms and monitoring their performance.
Duration : 5 Hours
PRE MATHS REFRESHER
Pre-Math provides a refresher of essential math concepts, focusing on building confidence in foundational skills. The course covers basic arithmetic, sets, and functions as the necessary groundwork for future mathematical learning
Duration : 5 hours
CORE MATH FOUNDATIONS
This course teaches key math concepts for AI and data science, including numbers, equations, logic, change, and uncertainty.
Duration : 5 Hours
MACHINE LEARNING MATH
Machine Learning Math builds a deep understanding of ML models through core mathematical principles and hands-on problem solving. Key topics include regression, logistic regression, PCA, and loss functions fundamental to model evaluation and optimization
Duration : 10 Hours
DEEP LEARNING MATH - Neural network core
Deep Learning Math explains the mathematical concepts powering deep neural networks, enabling a robust understanding of how deep learning models work. The course emphasizes matrix calculus for neural network operations, the chain rule and partial derivatives in backpropagation, activation function behavior, and advanced optimization techniques
Duration : 10 Hours
Domain Specific maths ( OPTIONAL )
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ADVANCED MATHS - RESEARCHER LEVEL ( OPTIONAL )
This advanced math course builds a strong foundation in key concepts for machine learning, covering topics like information theory, optimization, and tensor calculus. Learners apply these ideas to deep learning and probabilistic algorithms, with practical examples from AI research. The course strengthens skills in modeling complex, high-dimensional data
Duration : 10 Hours
LLM AGI Level - Frontier ( optional )
This frontier math course covers the fundamentals behind LLMs and AGI, focusing on attention mechanisms, embeddings, and scaling laws. Learners gain practical skills for applying transformers and information bottlenecks to modern AI tasks like search and model training. The curriculum balances theory and real-world innovation in deep learning and model design.
Duration : 10 Hours
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Courses
New Batch Starts : NOV 2025
DURATION : 2 Days
TIME: 10 AM - 1 PM ( Thu & Mon )
New Batch Starts : NOV 2025
DURATION : 20 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 5 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 5 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 5 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 10 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 10 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 10 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 10 hours
TIME : 8 - 10 PM ( Tue & Thu )
Explore
Domain Specific Maths
New Batch Starts : NOV 2025
DURATION : 4 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 3 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 3 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
DURATION : 3 hours
TIME : 8 - 10 PM ( Tue & Thu )
New Batch Starts : NOV 2025
