Generative AI & Advanced Data Science

Overview: This advanced course focuses on the latest trends in AI, particularly generative models and natural language processing (NLP). Students will also learn how to implement and deploy AI models on the cloud with Azure and apply them in business contexts through a capstone project.

Modules:

1. Tableau

• Create advanced visualizations and dashboards with Tableau.

2. Generative AI

• Encoder-Decoder models for NLP applications.
• Transformers: Understand the architecture and use cases of transformer models.
• Introduction to Generative Adversarial Networks (GANs)
• GPT models for text generation.

3. Big Data

• Introduction to big data technologies and frameworks like Hadoop and Spark.
• Analyze large datasets efficiently using these tools.

4. Azure Fundamentals

• Deploy AI models on Microsoft Azure.
• Explore cloud services for machine learning and data storage.

5. Capstone Project:

• A comprehensive project where students solve a real-world business problem using AI tools and techniques.

Tools:

• Tableau: For business reporting and data visualization.
• Python (NLTK, SpaCy, PyTorch, TensorFlow, Keras):For NLP and generative AI.
• Spark: For handling big data
• Azure: For cloud-based AI solutions and model deployment.
• GitHub: For collaboration and version control.

What You’ll Learn:

• Tableau: Build stunning visualizations and dashboards.
• NLP: Process and analyze text using NLTK, SpaCy, and tools for web scraping like Beautiful Soup and Selenium.
• Generative AI: Explore GANs, transformers, GPT models, and more.
• Azure Fundamentals: Deploy and manage AI models in the cloud.
• Big Data: Introduction to technologies like Hadoop and Spark for handling and analyzing large datasets.
• Capstone Project: Apply everything you’ve learned to solve a real-world problem.

Best For: Experienced data professionals aiming to specialize in AI and cloud technologies.

Job Prospects:

• AI Research Scientist: Conduct research and develop new AI technologies and models.
• Data Architect: Design and manage data systems and architecture.
• Cloud Data Engineer: Build and manage data solutions on cloud platforms like Azure.
• Big Data Engineer: Develop and implement big data solutions using technologies like Hadoop and Spark.