FULL-STACK DATA SCIENCE WITH GEN AI

Full-Stack Data Science with Generative AI

Unlock the future of data science with our comprehensive course on Full-Stack Data Science integrated with Generative AI. This program is designed to equip you with the skills to handle the entire data science lifecycle, from data collection, wrangling, and analysis, to deploying machine learning models and creating AI-driven applications.

What You’ll Learn:

• Data Handling & Preparation: Techniques for collecting, cleaning, and preprocessing data.
• Exploratory Data Analysis (EDA): Visualization and statistical methods to uncover insights.
• Machine Learning & Deep Learning: Build predictive models using Python, TensorFlow, PyTorch, and Scikit-Learn.
• Generative AI: Explore cutting-edge AI technologies, including large language models (LLMs), image generation (GANs, DALL·E), and text generation tools like GPT.
• Full-Stack Development: Learn to develop, deploy, and scale AI-powered applications using modern cloud platforms (AWS, Azure) and web technologies (React, Flask, Docker).
• Model Deployment & MLOps: Techniques for continuous integration, deployment, and monitoring of AI models in production environments.
• AI Ethics & Responsible AI: Understand the ethical implications and how to ensure fairness and transparency in AI systems.

Who is this course for?

• Aspiring data scientists looking to build expertise in the full data science stack.
• AI enthusiasts eager to explore Generative AI technologies.
• Software developers aiming to integrate machine learning and AI into their applications.
• Professionals interested in the end-to-end data science pipeline, from data wrangling to deployment.

Why Enroll?

• Hands-on projects that simulate real-world scenarios.
• Mentorship from industry experts in both data science and AI.
• Access to cutting-edge AI tools and frameworks.
• Certificate upon completion to boost your career in AI and Data Science.

Prerequisites:

• Basic knowledge of Python programming.
• Familiarity with data science fundamentals is helpful but not required.