Course Outline
Introduction to AI for Software Development
- Distinguishing between Generative AI and 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 tools (e.g., GitHub Copilot, CodeGeeX).
- Predicting code bugs and vulnerabilities prior to deployment.
- Automating code reviews and receiving optimization suggestions.
Building Predictive Models for Software Applications
- Understanding time-series forecasting and predictive analytics.
- Implementing AI models for demand forecasting and anomaly detection.
- Utilizing 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 using diffusion models.
Deploying AI Models in Real-World Applications
- Hosting AI models via 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 on 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
- A solid understanding of basic software development concepts.
- Experience with any programming language (Python is recommended).
- Familiarity with machine learning or AI fundamentals (recommended but not mandatory).
Target Audience
- Software developers.
- AI/ML engineers.
- Technical team leads.
- Product managers interested in AI-powered applications.
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3900 € + VAT*
Contact us for an exact quote and to hear our latest promotions
Testimonials (2)
The interactive style, the exercises
Tamas Tutuntzisz
Course - Introduction to Prompt Engineering
A great repository of resources for future use, instructor's style (full of good sense of humor, great level of detail)
