100735 - Virginia Tech Artificial Intelligence / Machine Learning (AI/ML) Bootcamp

Overview

The Virginia Tech AI and Machine Learning Bootcamp is designed for students to pursue high-quality tech education while continuing to balance work or other commitments. After 234 hours of synchronous instruction, participants will learn:

• Statistics Essentials for Data Science: Applied the principles of data science in real-world scenarios, emphasizing ethical practices and effective decision-making to drive data-informed outcomes
• Programming Basics: Gained hands-on experience with Python, mastering the skills to load, store, and manipulate data—essential for data analysis and problem-solving
• Applied Data Science with Python: Gained a deep understanding of data science processes, including data wrangling, exploration, advanced statistical analysis, and hypothesis building/testing, to effectively analyze and interpret data
• Machine Learning: Learned and deployed machine learning algorithms, models, and applications, gaining the ability to design and implement solutions that utilize predictive analytics and intelligent automation
• Deep Learning: Explored and implemented deep learning techniques using neural networks, creating, and optimizing models to solve complex business challenges
• Generative AI & Prompt Engineering: Investigated generative AI technologies, such as ChatGPT, and developed prompt engineering skills to leverage AI effectively and ethically for business and creative applications

The learners can gain the ability to:

• Implement data science principles in practical settings, ensuring ethical decision-making
• Utilize Python to handle and manipulate data, forming the foundation for robust data analysis
• Perform data wrangling, statistical analysis, and hypothesis testing to derive insights and drive decision-making
• Apply machine learning algorithms to build and deploy models that address business and research problems
• Develop deep learning models using neural networks to optimize performance in predictive analytics
• Effectively use generative AI and prompt engineering techniques to enhance business processes, while considering ethical implications

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