Course Syllabus
Download SyllabusModule 1: Web Development Basics
- HTML5 – Structure and semantic tags
- CSS3 – Styling, layouts, animations
- JavaScript – Functions, DOM manipulation, ES6 concepts
- Bootstrap – Responsive design and UI components
Module 2: Backend Development
- Core Python – Syntax, data structures, OOP concepts
- Advanced Python – Generators, decorators, exception handling, multithreading
- Django Framework – MVC architecture, authentication, REST API development
- Flask (Introduction) – Lightweight framework for microservices
Module 3: Database Management
- MySQL – Queries, joins, stored procedures
- MongoDB – NoSQL databases for AI-based projects
- Integration of databases with Python/Django
Module 4: Artificial Intelligence & Machine Learning
- Machine Learning – Supervised, unsupervised, and reinforcement learning
- Data Preprocessing & Feature Engineering
- Model building using Scikit-learn
- Advanced ML – Ensemble methods, model optimization, hyperparameter tuning
Module 5: Deep Learning & Advanced AI
- Neural Networks – Feedforward and backpropagation
- TensorFlow & Keras – Deep learning frameworks
- Convolutional Neural Networks (CNNs) – Image recognition & classification
- Recurrent Neural Networks (RNNs) & LSTMs – Sequence modeling, time-series data
- Generative Adversarial Networks (GANs) – Advanced AI applications
- Natural Language Processing (NLP) – Sentiment analysis, chatbots, text mining
- Computer Vision with OpenCV – Face recognition, object detection
Module 6: AI Deployment & Cloud Integration
- Model Deployment with Flask/Django REST APIs
- Docker for AI model packaging
- Cloud Platforms (AWS / Azure / GCP) – AI and ML services integration
- MLOps – Model lifecycle management and monitoring
Module 7: Capstone Projects & Case Studies
- AI-powered Chatbot Development
- Image Classification using CNNs
- Predictive Analytics for Business
- Recommendation Systems (e-commerce, media, etc.)
- AI Model Deployment on Cloud
The Artificial Intelligence Engineering Course Syllabus at SLA Institute is really good for people who come from places like information technology, business, and marketing. The Artificial Intelligence Engineering Course Syllabus has a lot of hands-on work and real projects. This helps people learn Artificial Intelligence skills that they can actually use. If people pick the Artificial Intelligence course, they can learn what they need to know to get the job they want in areas like data science, cybersecurity, making products, and more. This means people can do well in the Artificial Intelligence field.
