AI Engineering
Transform your software engineering skills into AI expertise in 12 weeks
Course Overview
The AI Engineering program is designed specifically for Software Development Engineers who want to transition into the high-demand field of AI.
You'll learn to design, build, and deploy AI systems while leveraging your existing programming expertise. By the end of this course, you'll have a portfolio of AI projects and the skills needed to excel in roles like Machine Learning Engineer, AI Engineer, or AI Application Developer.
Course Format
- Fully online self-paced course
- Pre-recorded video lectures
- Complete source code provided
- Hands-on projects included
- Learn at your own pace
Prerequisites
Programming Skills
Proficiency in Python programming and familiarity with data structures and algorithms
Data Knowledge
Basic understanding of databases, data manipulation, and analysis
Math Background
Comfort with basic linear algebra, calculus, and probability concepts
Development Experience
1+ years of software development experience in any programming language
Course Pricing
Regular Price: ₹5,000
Special Offers:
- Summer 2025 Early Bird Price: ₹999 (Limited time)
- Student Discount: 50% off with valid .edu email
Course Curriculum
Module 1: Foundations of AI & ML
- Introduction to AI concepts and applications
- Python for AI: NumPy, Pandas, and visualization libraries
- Machine Learning fundamentals
- Data preprocessing and feature engineering
- Project: Predictive analysis system for time series data
Module 2: Deep Learning Fundamentals
- Neural network architecture and components
- TensorFlow and PyTorch frameworks
- Training and optimization techniques
- Convolutional Neural Networks (CNNs)
- Project: Image classification system
Module 3: Natural Language Processing
- Text processing and representation
- Language models and embeddings
- Transformer architectures
- Building applications with Hugging Face
- Project: Intelligent conversational agent
Module 4: Generative AI & Advanced Topics
- Generative models (GANs, VAEs)
- Diffusion models
- Large Language Models (LLMs)
- Prompt engineering techniques
- Project: Text-to-image generation system
Module 5: MLOps & AI System Design
- ML system architecture and design patterns
- Model deployment and serving
- Monitoring and maintenance
- Cloud platforms for AI (AWS, GCP, Azure)
- Project: End-to-end ML system with CI/CD pipeline
Module 6: Capstone Project
- Project planning and requirements gathering
- Architecture design and implementation
- Testing and evaluation
- Deployment and demonstration
- Final presentation and portfolio development
Frequently Asked Questions
How much programming experience do I need?
We recommend at least 1 year of software development experience. You should be comfortable with Python programming, as it's the primary language used throughout the course. If you're not familiar with Python but have experience with other languages, we provide pre-course materials to help you get up to speed.
What is the time commitment?
The course requires about 15-20 hours per week. This includes 6 hours of live sessions (typically held evenings or weekends), plus additional time for assignments, projects, and self-study. Many of our students complete the course while working full-time jobs.
Will I receive a certificate upon completion?
Yes, all graduates receive an official LaunchPy AI Engineering certificate upon successful completion of the course requirements. More importantly, you'll graduate with a portfolio of AI projects that demonstrate your skills to potential employers.
Are there any prerequisites for joining the course?
Yes, applicants should have software development experience, basic knowledge of Python programming, and foundational understanding of data structures and algorithms. Some background in mathematics (algebra, calculus, and probability) is also beneficial. We provide pre-course materials to help you prepare.
Enroll in AI Engineering
Next cohort starts on April 15, 2025 — Limited spots available