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via Udemy |
Go to Course: https://www.udemy.com/course/xgboost-python-r/
Certainly! Here's a detailed review and recommendation for the Coursera course "10 Days of Prompt Engineering, Generative AI, and Data Science": --- **Course Review: 10 Days of Prompt Engineering, Generative AI, and Data Science on Coursera** **Overview:** This intensive 10-day course, crafted by instructor Diogo, offers a comprehensive journey into Prompt Engineering, Generative AI, and Data Science. Designed for learners eager to rapidly develop practical skills, the course combines live sessions, hands-on labs, and real-world projects within just 14 hours and 30 minutes of video content. Its structure ensures a progressive learning curve, from foundational concepts to advanced topics, making it suitable for both beginners and those with some AI background. **Content and Structure:** The curriculum is carefully curated to cover key aspects of AI and data science: - **Prompt Engineering:** Understanding transformers, attention mechanisms, and crafting effective prompts. - **Generative AI:** Mastery of workflows with tools such as Google Colab, Jupyter Notebook, and LM Studio, as well as fine-tuning models and system messages. - **API Integration:** Practical experience with the OpenAI API for text and image generation. - **Machine Learning:** In-depth modules on Random Forests and XGBoost, including parameter tuning, SHAP values, and application scenarios like customer satisfaction analysis. - **Future Technologies:** A glimpse into upcoming developments like Reasoning in LLMs and AI automation with CrewAI. Each day builds on the previous, culminating in hands-on projects like creating a Rock-Paper-Scissors AI and customer satisfaction models, which solidify theoretical understanding through practical application. **Strengths:** - **Practical Focus:** The inclusion of projects and labs ensures that learners can apply skills immediately. - **Lifetime Updates:** Continuous content improvements mean the course remains current as AI tools evolve. - **Comprehensive Coverage:** From basic prompt design to advanced ML techniques and future AI agents, the course covers a broad spectrum. - **Community Engagement:** Opportunities for feedback and discussions foster a supportive learning environment. **Areas for Improvement:** - The course assumes some basic familiarity with programming and AI concepts; absolute beginners might need supplementary resources. - Some advanced topics like Reasoning in LLMs and AI Agents are scheduled for future modules, which may require learners to seek additional learning material in the meantime. --- **Recommendation:** If you're looking to swiftly acquire practical skills in Prompt Engineering and Generative AI, this course is highly recommended. Its project-oriented approach, combined with a clear pathway from fundamentals to advanced concepts, makes it ideal for tech enthusiasts, aspiring data scientists, and AI practitioners. The lifetime updates and emphasis on real-world applications add significant value, ensuring your learning remains relevant and applicable. **Final Verdict:** *A highly effective and well-structured course for anyone serious about mastering Prompt Engineering, Generative AI, and Data Science in a short period. Enroll now to stay at the forefront of AI innovation and build a compelling portfolio of projects.* --- Would you like me to help you draft a personalized review or a promotional post based on this?
Welcome to the 10 Days of Prompt Engineering, Generative AI, and Data Science CourseGet hands-on with Prompt Engineering, Generative AI, and Data Science in just 10 days. I'm Diogo, and I've structured this course to take you from basics to advanced topics quickly. We'll cover live sessions, hands-on labs, and real-world projects-all in 14 hours and 30 minutes of published video content. You'll also receive lifetime updates so your learning never goes stale.You will build a portfolio of project on topics like:Prompt Engineering Fundamentals: Understand transformers, attention mechanisms, and how to structure prompts for optimal performance.Generative AI Workflows: Master tools like Google Colab, Jupyter Notebook, LM Studio, and learn how to fine-tune system messages and model parameters.OpenAI API for Text & Images: Integrate the OpenAI API into Python projects, explore parameters for better text generation, and tap into image generation (coming soon).Machine Learning with XGBoost & Random Forest: Explore advanced ML topics, including parameter tuning, SHAP values, and real-world approaches to customer satisfaction modeling.AI Agents with CrewAI: Dive into the next wave of AI automation (coming in Q1 2025).COURSE BREAKDOWNIntroductionMeet your instructor, download course materials, set up your environment (Google Colab, Jupyter Notebook, RStudio).Preview the core projects we'll tackle.Day 1 - Basics of Prompt EngineeringLearn about transformers, attention, and chain-of-thought prompting.Experiment with LM Studio to practice explicit instructions, one-shot, and few-shot techniques.Day 2 - System Messages & LLM ParametersTokenization, system messages, and parameter tuning.Break the system message (on purpose) to see how LLMs respond, then learn how to guide them back.Days 3 - Prompt Engineering for better reasoningProven ways to improve the reasoning in LLMs.Overcoming LLM HallucinationsDay 4 -Reasoning LLMs - Coming in Q1 2025How Reasoning Works in LLMsPrompt Injection for LLMs like the O1.A hot take on whether LLMs can reason or not.Day 5 - OpenAI API for Text GenerationIntegrate the OpenAI API in Python.Adjust temperature, handle few-shot learning, and refine your text generation workflow.Day 6 - CAPSTONE PROJECT: OpenAI APIBuild a "Rock-Paper-Scissors" AI.Create new strategies, test temperature parameters, and see how GPT adapts.Days 7 - OpenAI API for ImagesFee images via links and encoded to the Multimodal LLMAdd Web-browsing capabilities to the LLMDay 8 - Random Forest for Customer SatisfactionEnd-to-end project on gathering actionable insights on customer satisfaction.Guide on how to build a great chart.Day 9 - XGBoostDiscover XGBoost in both Python and R.Handle data processing, parameter tuning, cross-validation, and SHAP values for model interpretation.Day 10 - AI Agents with CrewAIComing in Q2 2025-learn to build AI agents that automate tasks and collaborate efficiently.WHY ENROLL NOW?Lifetime Updates: You get all future course modules automatically, including advanced sections scheduled for 2025.Practical Projects: Apply what you learn in real-world scenarios (Rock-Paper-Scissors AI, XGBoost for customer satisfaction).Structured Curriculum: Each day is designed to build on the previous one, speeding up your learning and progress.Community & Feedback: Engage in discussions, get direct feedback, and influence new content updates.Ready to accelerate your Prompt Engineering, Generative AI, and Data Science skills?Sign up now and gain immediate access to all published content, including the future modules. Let's start building the future of AI together!