Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Introduction to AI for Software Development
- What is Generative AI vs Predictive AI
- Applications of AI in coding, analytics, and automation
- Overview of LLMs, transformers, and deep learning models
AI-Assisted Coding and Predictive Development
- AI-powered code completion and generation (GitHub Copilot, CodeGeeX)
- Predicting code bugs and vulnerabilities before deployment
- Automating code reviews and optimization suggestions
Building Predictive Models for Software Applications
- Understanding time-series forecasting and predictive analytics
- Implementing AI models for demand forecasting and anomaly detection
- Using Python, Scikit-learn, and TensorFlow for predictive modeling
Generative AI for Text, Code, and Image Generation
- Working with GPT, LLaMA, and other LLMs
- Generating synthetic data, text summaries, and documentation
- Creating AI-generated images and videos with diffusion models
Deploying AI Models in Real-World Applications
- Hosting AI models using Hugging Face, AWS, and Google Cloud
- Building API-based AI services for business applications
- Fine-tuning pre-trained AI models for domain-specific tasks
AI for Predictive Business Insights and Decision-Making
- AI-driven business intelligence and customer analytics
- Predicting market trends and consumer behavior
- Automating workflow optimizations with AI
Ethical AI and Best Practices in Development
- Ethical considerations in AI-assisted decision-making
- Bias detection and fairness in AI models
- Best practices for interpretable and responsible AI
Hands-On Workshops and Case Studies
- Implementing predictive analytics for a real-world dataset
- Building an AI-powered chatbot with text generation
- Deploying an LLM-based application for automation
Summary and Next Steps
- Review of key takeaways
- AI tools and resources for further learning
- Final Q&A session
Requirements
- An understanding of basic software development concepts
- Experience with any programming language (Python recommended)
- Familiarity with machine learning or AI fundamentals (recommended but not required)
Audience
- Software developers
- AI/ML engineers
- Technical team leads
- Product managers interested in AI-powered applications
21 Hours
