Fundamentals of GenAI [Live Course]
Aug 20th – Aug 30th
Tue & Thurs 12pm-1:30p EST
AI isn’t going away. Level up your skills and advance your career!
Gain essential AI knowledge and hands-on experience with the tools reshaping our world. This course is designed to equip you with the skills to ideate, challenge, test, and create AI-driven strategies that drive real business results.
—Previous students have gone on to build internal chatbots, RAG models, and on-premise task-specific solutions with significant business impact.
Accessible Technical Content (finally)
Dive into the wonderful world of data science, machine learning, and AI.
Let’s demystify the technical parts of Data Science with easy to understand guides, hands-on projects, easy-to-follow tutorials and customized support.
Statistics
Master the art of decision-making through our Statistics course, where you’ll learn to analyze and interpret complex data with precision.
Python
Designed to equip you with the coding skills essential for modern data manipulation and analysis.
Data Fundamentals
Grasp the core concepts of data handling, processing, and visualization, setting a solid foundation for your data science journey.
Machine Learning
Unlock the power of predictive algorithms, where you’ll learn to build models that adapt and learn from data.
AI 101 Workshops
Designed for teams and organizations, this workshop offers tailored hands-on training, interactive exercises, and expert guidance on AI fundamentals.
Whether you’re looking to upskill your staff or explore new possibilities with AI, our in-house workshop aligns with your unique goals and needs, delivering an engaging learning experience customized to provide maximum value. Get your team up to AI speed with a Data Sci 101 AI Workshop!
Learn by Doing
Embrace a hands-on approach where theory meets practice.
Engage in real-world projects, interactive exercises, and collaborative challenges that not only teach you the concepts but immerse you in the actual process of data science. It’s not about memorizing facts; it’s about applying knowledge, solving problems, and growing through experience.
Achieve Your Goals
We believe in learning that translates into real-world success.
Practical knowledge and actionable insights ensures that what you gain here isn’t just theoretical but truly impactful. Your aspirations deserve more than just traditional methods; they deserve a roadmap to genuine achievement.
“Britney’s AI workshop was eye-opening about how we can apply AI in our work and daily lives.
She took dense topics around LLMs (large language models), generative vs descriminitaive AI, and turned them into easy-to-digest, interesting topics that were fun to learn about. I came away from the session much better informed about AI and how it should/shouldn’t be used.”
Amanda Middeldorp, Marketing Manager at Pure SEO
FAQs
What if I have no coding experience?
No problem! Our content will walk you through any programming examples + our notebooks cannot ‘break your computer’ or cause any issues so we strongly encourage you to try! 🙂
What is python used for?
Python is a versatile programming language widely used for web development, automation, data analysis, AI, and more. Its simplicity and readability make it a popular choice for both beginners and seasoned developers.
What is data science?
Data science is a multidisciplinary field that uses scientific methods, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It combines aspects of statistics, computer science, and domain-specific knowledge to provide actionable results.
What is machine learning?
Machine Learning (ML) is a subset of artificial intelligence that enables computers to learn and make decisions from data without being explicitly programmed.
What does a data scientist do?
A data scientist extracts valuable insights from data. They gather, analyze, and interpret datasets using analytical and machine learning techniques. Their role is pivotal in helping businesses make data-driven decisions.
How to learn data science?
Begin with the fundamental principles of mathematics, focusing on linear algebra and statistics. Engaging with real-world datasets or setting specific objectives can improve retention & practical understanding of data science concepts.
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