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Duration 21 hours
Course Outline
Introduction to AI in Software Development
- Distinguishing between Generative AI and Predictive AI
- The role of AI in coding, data analytics, and automation
- An overview of LLMs, transformers, and deep learning architectures
AI-Assisted Coding and Predictive Development
- Leveraging AI for code completion and generation (e.g., GitHub Copilot, CodeGeeX)
- Identifying code bugs and vulnerabilities pre-deployment
- Streamlining code reviews and generating optimization insights
Building Predictive Models for Software Applications
- Understanding time-series forecasting and predictive analytics
- Creating AI models for demand forecasting and anomaly detection
- Using Python, Scikit-learn, and TensorFlow for predictive modeling
Generative AI for Text, Code, and Image Creation
- Working with GPT, LLaMA, and other prominent LLMs
- Generating synthetic data, text summaries, and technical documentation
- Producing AI-generated images and videos using diffusion models
Deploying AI Models in Production Environments
- Hosting AI models on platforms like Hugging Face, AWS, and Google Cloud
- Developing API-based AI services for business integration
- Fine-tuning pre-trained models for domain-specific tasks
AI for Business Intelligence and Decision-Making
- Enhancing business intelligence and customer analytics with AI
- Predicting market trends and consumer behavior patterns
- Optimizing business workflows through AI automation
Ethical AI and Responsible Development Practices
- Addressing ethical considerations in AI-assisted decision processes
- Detecting bias and ensuring fairness in AI models
- Adopting best practices for interpretable and responsible AI
Hands-On Workshops and Case Studies
- Applying predictive analytics to real-world datasets
- Building an AI-powered chatbot with text generation capabilities
- Deploying an LLM-based application for workflow automation
Summary and Path Forward
- Recap of key concepts and takeaways
- Recommended AI tools and resources for continued learning
- Final Q&A session
Requirements
- A solid understanding of fundamental software development concepts.
- Proficiency in at least one programming language (Python is highly recommended).
- Basic familiarity with machine learning or AI concepts (recommended, but not mandatory).
Target Audience
- Software developers
- AI/ML engineers
- Technical team leads
- Product managers exploring AI-powered application development
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 4350 € + VAT*
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Testimonials (4)
Understanding of AI and LLM. How it works and ehat the watchouts and opportunities are!
Henk Jan Beltman - genuine business
Course - Advanced AI Concepts with Perplexity
Comprehensiveness about the backround; how to do a prompt.
Olaf Kannt - Helios Klinikum Krefeld
Course - Generative AI and Prompt Engineering in Healthcare
the tips and recommended prompts that we can take away from this training
Lee Mei Lin - ST Engineering IHQ Pte Ltd
Course - InVideo AI: Creating Engaging Short-Form Videos
use of proper and effective prompt
