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Have you ever wondered how goods get to us so quickly after we order them? One word: Logistics! In this introductory course on supply chain logistics, I take you on a journey through this fascinating backbone of global trade. We will look at the three main building blocks of logistics networks: transportation, warehousing, and inventory. By the end of this course, you will be able to differentiate between the advantages and disadvantages of different modes of transportation. You will understand what goes into designing and building warehouse facilities. Finally, you will be able to choose the options that will allow you to create logistics networks that minimize costs and provide the highest levels of customer service. This is an introductory course designed to give you a head start on your logistics education. You do not need to have any formal education in logistics, but it will help if you have a basic understanding of business concepts. Join me as we explore logistics together! Are you interested in learning more advanced supply chain topics? Explore the Supply Chain Excellence MasterTrack™ Certification: https://www.coursera.org/mastertrack/supply-chain-excellence-rutgers

If you are a software developer who wants to build scalable AI algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning with Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source machine learning framework. In Course 2 of the deeplearning.ai TensorFlow Specialization, you will learn advanced techniques for improving the computer vision model you built in Course 1. You will learn how to work with real-world images of different shapes and sizes, visualize an image’s journey through convolutions to understand how a computer “sees” information, plot loss and accuracy, and explore strategies to prevent overfitting, including padding and dropout. Finally, Course 2 will introduce you to transfer learning and how learned features can be extracted from models. Andrew Ng's Machine Learning course and Deep Learning Specialization teach the most important and fundamental principles of machine learning and deep learning. The new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement these principles, so you can start building and applying scalable models to real-world problems. For a deeper understanding of how neural networks work, we recommend the Deep Learning Specialization.

A recent survey found that 37% of teens say they have poor mental health. This 6-week course aims to address this mental health crisis by combining the best ideas from Dr. Laurie Santos’s popular Yale course, Psychology and the Good Life. In this course, you’ll learn what psychology teaches us about how to be happier, how to experience less stress, and how to succeed in high school and beyond. The lessons, plus short weekly “happiness homework” assignments, will ultimately prepare you to put these scientific findings into practice. The end goal is for you to feel better and develop healthier habits. Parents, teachers, and other professionals who support teens may also find this course helpful. Note: This course does not provide grades, credit, or Yale student status. THE SCIENCE OF HAPPINESS FOR TEENAGERS was made possible in part by generous funding from the ARTHUR M. BLANK Family Foundation and the JOHN TEMPLETON Foundation.

You’re almost there! This is the third and final course in the Google Business Intelligence Certificate. In this course, you’ll apply your understanding of stakeholder needs, plan and create BI visuals, and design reporting tools, including dashboards. You’ll also explore how to answer business questions with flexible and interactive dashboards that can monitor data over long periods of time. Google employees who currently work in BI will guide you through this course by providing hands-on activities that simulate job tasks, sharing examples from their day-to-day work, and helping you build business intelligence skills to prepare for a career in the field. Learners who complete the three courses in this certificate program will have the skills needed to apply for business intelligence jobs. This certificate program assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: - Explain how BI visualizations answer business questions - Identify complications that may arise during the creation of BI visualizations - Produce charts that represent BI data monitored over time - Use dashboard and reporting tools - Build dashboards using best practices to meet stakeholder needs - Iterate on a dashboard to meet changing project requirements - Design BI presentations to share insights with stakeholders - Create or update a resume and prepare for BI interviews

If there is a shortcut to becoming a Data Scientist, it is learning to think and act like a successful Data Scientist. In this course, you will learn and then apply a methodology that you can use to solve any data science problem. You will learn two well-known data science methodologies, the Foundational Data Science Methodology and the six-step CRISP-DM data science methodology, and learn how to apply these data science methodologies. Most successful data scientists follow these or similar methodologies when solving data science problems. Start by learning how to formulate a business/research problem Learn how data scientists obtain, prepare, and analyze data Learn how applying data science methodologies helps ensure that the data used to solve a problem is relevant and is manipulated correctly to solve the question Next, you will learn about building a data model, deploying that model, telling stories about the data, and getting feedback. You will think like a data scientist and develop your data science methodology skills using a real-world inspired scenario through sequential labs conducted in Jupyter Notebooks and using Python.

In this course, you will: - Learn about GANs and their applications - Understand the intuition behind the fundamental components of GANs - Explore and implement several GAN ​​architectures - Build conditional GANs capable of generating examples from specific categories The DeepLearning.AI Generative Adversary Networks (GANs) specialization provides a fascinating introduction to image generation with GANs, leading the way from fundamental concepts to advanced techniques in a simple and straightforward approach. It also covers social implications, including bias in ML and how to detect it, privacy preservation, and more. Build a comprehensive knowledge base and gain hands-on experience with GANs. Train your own model with PyTorch, use it to generate images, and evaluate various advanced GANs. This specialization provides an accessible path for students of all levels who want to enter the field of GANs or apply GANs in their own projects, even without prior exposure to advanced mathematics and machine learning research.

This course delves into the fundamental concepts related to Prompt Engineering and Generative AI. The course has subsections on Fundamentals of Prompt Engineering, Retrieval Augmented Generation, Fine-tuning a large language model (LLM) and Guardrails for LLM. Section on Prompt Engineering Fundaments : The first segment provides a definition of prompt engineering, best practices of prompt engineering and an example of a prompt given to the Gemini-Pro model with references for further reading. The second segment explains what streaming a response is from a large language model, examples of providing specific instructions to the Gemini-Pro model as well as temperature and token count parameters. The third segment explains what Zero-Shot Prompting technique is with examples using the Gemini Model. The fourth segment explains Few-shot and Chain-of-Thought Prompting techniques with examples using the Gemini Model. Subsequent segments in this section shall discuss setting up the Google Colab notebook to work with the GPT model from OpenAI and provide examples of Tree-of-Thoughts prompting technique, including the Tree-of-Thoughts implementation from Langchain to solve the 4x4 Sudoku Puzzle. Section on Retrieval Augmented Generation (RAG) : In this section, the first segment provides a definition of Retrieval Augmented Generation Prompting technique, the merits of Retrieval Augmented Generation and applying Retrieval Augmented Generation to a CSV file, using the Langchain framework In the second segment on Retrieval Augmented Generation, a detailed example involving the Arxiv Loader, FAISS Vector Database and a Conversational Retrieval Chain is shown as part of the RAG pipeline using Langchain framework. In the third segment on Retrieval Augmented Generation, evaluation of response from a Large Language Model (LLM) using the RAGAS framework is explained. In the fourth segment on Retrieval Augmented Generation, the use of Langsmith is shown complementing the RAGAS framework for evaluation of LLM response. In the fifth segment, use of the Gemini Model to create text embeddings and performing document search is explained. Section on Large Language Model Fine-tuning : In this section, the first segment provides a summary of prompting techniques with examples involving LLMs from Hugging Face repository and explaining the differences between prompting an LLM and fine-tuning an LLM. The second segment provides a definition of fine-tuning an LLM, types of LLM fine-tuning and extracting the data to perform EDA (including data cleaning) prior to fine-tuning an LLM. Third segment explains fine-tuning a pre-trained large language model on a task specific labeled dataset in detail. Section on Guardrails for Large Language Models: In this section, the first segment provides a definition of Guardrails as well as examples of Guardrails from OpenAI. In the second segment on Guardrails, examples of open source Guardrail implementations are discussed with a specific focus on GuardrailsAI for extracting information from text. In the third section, use of GuardrailsAI for generating structured data and interfacing GuardrailsAI with a Chat Model have been explained. Each of these segments has a Google Colab notebook included.

Artificial intelligence is the fastest growing field right now. This course combines Artificial intelligence and Javascript and takes you into the world of 2D game development and creating 2D AI games. There are too many job opportunities in this field today, and the scope is huge. Demand for AI programmers is increasing exponentially every day. Have you always wanted to learn artificial intelligence? Were you not able to do so because you never knew where to start? Is everything confusing out there? Then our course is the perfect solution to your problem. In our course, -> You'll earn the concepts of artificial intelligence, -> Delve more into theories and implementation by learning what MiniMax algorithm is, and how to implement it, -> Apply your new found knowledge to create a fully functional Artificial intelligence that can play a Tic Tac Toe game against expert human players. -> All the while learning, and becoming proficient in Javascript, HTML5 canvas, HTML5, CSS3, front end web development and 2D game development. Why take this course? You'll be able to: 1. Learn the basics of artificial intelligence, its terminologies, the various terms used in the field etc. 2. Learn what the MiniMax algorithm is and how it's used in developing Zero sum artificial based games in the real world. 3. Learn how to apply the MiniMax algorithm in a 2D web game like Tic Tac Toe 4. Learn how to create an unbeatable AI opponent in your games 5. Learn the basics of Javascript and HTML5 canvas and how to apply it in your Tic Tac Toe game project 6. Improve your logical problem solving skills 7. Create a complete dynamic Tic Tac Toe game app with an unbeatable AI with Javascript, HTML5 canvas and css 8. Improve your web app development, web game development & javascript skills 9. Improve your front end design and development skills 10. How to design the game logic for the game and implement it as code 11. Learn HTML5, CSS3 and much more while developing your game 12. Add artificial intelligence to your resume with this project as proof of your knowledge How is this course designed? I've made this course as easy to understand as possible. I've structured it in such a way that each section will handle one major part of the course. Introduction: This is where we'll explain how the game works, it's various features and what we'll be using to achieve the same results. Module 1: We'll explain the basics of artificial intelligence and it's various terminologies. We'll put the ground work you'll need to understand the further concepts explained in this course. Module 2: We'll explain what the MiniMax alrogithm is and how it's implemented. We'll use pictorical and graphical representation to explain the concept with 2 detailed examples. We'll also explain the Pseudocode of the algorithm. Module 3: We'll explain how the MiniMax algorithm can be implemented in creating an artificial intelligence based player (computer player) for a Tic Tac Toe game. We'll explain the concept with another pictorical representation of the entire process. Module 4: We'll delve into Javascript and HTML5 canvas concepts that are related to the project we'll be creating. I'll only cover concepts that we'll need for our game's Javascript code though. If you already know the basics, you can skip this module. Module 5: We'll be teaching you how to create the bare bones of the app with HTML5. The result will be a page with all the elements we need in our game, devoid any colors or design elements. After that, we'll "beautify" our app. We'll be using CSS elements to give our game colors and styles. At the end of this module, we'll have a Tic Tac Toe web game that'll look like the final result, albeit one that is not playable yet. Module 6: We'll introduce a step by step algorithm that explains what we'll be doing while creating the Javascript part of our code. Module 7: We'll be delving into Javascript & HTML5 canvas code of our game in this module, and we'll teach you how to make the game playable (let the user draw on the canvas and display the game results) in here. In this part, we'll create the necessary code to make the human player play the game on the app. Module 8: This would be the meat of the course. In this module, we'll be applying the MiniMax algorithm with relevant Javascript code to create an artificial intelligence that can play against the human player (the web user). This course is for you if: 1. If you like learning by doing rather than hours of boring theoretical lectures. 2. If you've always been interested in artificial intelligence, but you're intimidated by the sheer amount of information available on the subject. 3. If you want a simplified way of starting out with artificial intelligence. 4. If you want to pad your resume with an eye-catching skill, a.k.a applied artificial intelligence. 5. If you don't want to just learn theories but start applying it to create an application you can brag about in your resume. You'll be learning the concepts of MiniMax algorithm, a very important algorithm in artificial intelligence, while applying it to create your AI based Tic Tac Toe game. What better way to learn a concept that's considered difficult for most people? 6. If you're a complete newbie to the world of web development, or just programming in general, and would like to start creating software with the help of a beginner-friendly course. You'll learn the basics of everything used in this project (HTM5, CSS3, Javascript, HTML canvas). We'll be explaining every single line of code we'll be using in this course, so you won't feel lost. 7. If you have the passion for programming, and know the basics of HTML5 and CSS, but you're stuck on the practical aspects of it. Turn your theoretical knowledge into practical knowledge with our course. 8. If you want to delve into the exciting world of front end web app development, this course will take you a couple steps further in the right direction. 9. If you're a Javascript web developer who just wants to try out a new project. Our course welcomes coders of every level, from absolute beginners, to pros. By adding artificial intelligence to this project, we've tried to make it interesting for programmers of every level. 10. If you want to learn HTML5 based 2D game development. So, what are you waiting for? Get this course today, and begin your journey into the wonderful world of Artificial Intelligence and web game development!

Embark on a transformative learning journey with "No-Code AI for Agriculture Professionals," a comprehensive course designed to empower participants with the knowledge and practical skills needed to embrace the future of agriculture infused with artificial intelligence. This course goes beyond traditional coding, introducing a revolutionary no-code approach to seamlessly integrate AI into agricultural practices. Objectives of the Course: 1. Foster AI Awareness: - Immerse participants in understanding the omnipresence of AI in their surroundings. - Cultivate awareness of how AI shapes and enhances various aspects of daily life, especially in the agricultural sector. 2. Explore Diverse AI Applications in Agriculture: - Provide an in-depth exploration of the diverse applications of AI in modern agriculture. - Showcase real-world examples of AI-driven innovations transforming the agricultural landscape. 3. AI Fundamentals and Classification: - Lay the groundwork by imparting fundamental knowledge of AI, its classifications, and key components. - Equip participants with the foundational understanding necessary for advanced applications. 4. Dispelling AI Myths: - Address and dispel common myths surrounding AI to foster informed decision-making. - Empower participants to differentiate between myths and realities in the AI realm. 5. No-Code AI Platform Exploration: - Introduce No-Code AI platforms, unravelling their functionalities and ease of use. - Demonstrate how these platforms eliminate the need for coding while enabling powerful AI integration. 6. Practical Integration in Agriculture: - Guide participants in applying No-Code AI platforms to integrate AI seamlessly into practical agriculture use cases. - Facilitate hands-on experience, ensuring proficiency in implementing AI solutions without coding complexities. 7. Job Opportunities in AI-Driven Agriculture: - Illuminate the evolving landscape of job opportunities in the agriculture sector fueled by AI. - Provide insights into emerging roles and skillsets demanded by the industry. 8. Next Course Preview: - Offer a sneak peek into the next course, tantalizing participants with over 30 diverse AI projects in agriculture. - Ignite anticipation for advanced learning and hands-on exploration of cutting-edge AI applications. Expected Outcomes: Upon completion of the course, participants will: - Develop heightened awareness of AI's pervasive influence in daily life. - Acquire an in-depth comprehension of AI applications in agriculture. - Gain a solid foundation in AI fundamentals, classifications, and key components. - Recognize and counter prevalent myths associated with AI. - Become proficient in utilizing No-Code AI platforms for practical applications. - Implement AI in real-life agriculture use cases without the need for coding. - Possess insights into potential future job opportunities in the AI-driven agricultural sector. - Eagerly anticipate advanced learning through a preview of the next course featuring 30+ AI projects in agriculture. Enroll today and be at the forefront of the agricultural revolution, where technology meets the soil with no-code AI expertise!

Unlock the potential of Artificial Intelligence while ensuring ethical integrity and societal benefit with our comprehensive course, "Responsible AI: Principles, Practices, and Applications." This course is designed to provide you with a deep understanding of the key principles and practical strategies needed to develop, implement, and manage AI technologies responsibly. What You'll Learn: - The foundational principles of responsible AI, include fairness, accountability, transparency, and privacy. - Ethical implications of AI technologies and their impact on society. - Best practices and common pitfalls in AI development and deployment through real-world case studies. - Skills to create and implement AI systems adhering to ethical guidelines and regulatory standards. - Techniques for auditing and monitoring AI systems to ensure ongoing compliance with responsible AI principles. - The importance of diverse and inclusive data in reducing biases and enhancing the fairness of AI models. Who Should Enroll: This course is perfect for Business Owners and Business Leaders, AI enthusiasts, data scientists, machine learning engineers, technology managers, and anyone interested in the ethical deployment of AI technologies. Whether you are a professional seeking to enhance your AI projects' integrity or a beginner aiming to understand the responsible use of AI, this course will equip you with the necessary knowledge and skills. Why Enroll: - Gain insights from industry experts and thought leaders in AI ethics. - Learn through interactive lessons, hands-on projects, and real-world examples. - Access valuable resources, including tools and frameworks for responsible AI development. - Join a community of like-minded professionals dedicated to the ethical advancement of AI. Enrol now and take the first step towards mastering responsible AI practices, ensuring your AI solutions are not only innovative but also ethical and impactful.

Hey Storytellers, It's Time to Revolutionize Your Writing in 2024! Welcome to the future of fiction writing! Imagine having a ChatGPT buddy who knows your story inside out. That's exactly what you'll get in our latest and greatest course: "AI-Powered Fiction: Craft Amazing Novels with ChatGPT." It's like having a coffee chat with AI about your novel, but even better. Here’s what you’ll learn in this course: - Got Writer’s Block? Wave goodbye to it! With AI, you'll find ideas flowing like a never-ending stream. - Plot Twists and Turns? You'll master the art of crafting gripping stories with structures like the Hero’s Journey and our 24-chapter blueprint, all with a little help from your AI pal. - Characters That Feel Real? Absolutely! Dive deep into their psyches and bring them to life in ways you never thought possible. - Dialogue That Pops: Learn how to mix your unique voice with AI’s savvy to create conversations that leap off the page. What's Super Cool in 2024? You'll create your very own ChatGPT bot! No coding is required. This isn't just any bot – it's one that's been custom-made by you for your unique story. It's like having a secret weapon in your writing toolkit, giving you a creative edge that's just plain awesome. Meet Your Storytelling Guide: Michael Wood, M.Ed., M.S. - Your Personal Storytelling Guru: Michael's not just an instructor; he's your guide on this exciting journey. With a rich background in English literature and a passion for fiction, he’s the real deal. - Experience Galore: From public school teaching to navigating the adventures of being an Army veteran, Michael brings a treasure trove of experiences to the table. - Your Writing Coach and Cheerleader: He’s here to share his wisdom, offer practical tips, and cheer you on every step of the way. Think of Michael as your personal writing coach. Why You’ll Love This Course: - Perfect for All Levels: Whether you’re just starting out or you’re a seasoned pro, there’s something here for everyone. - Fun, Hands-On Learning: With exercises and a super handy workbook, you'll be applying what you learn in no time. - A Community of Fellow Writers: Join the club! You'll be part of a group of like-minded souls, all on this exciting writing journey. Ready to jump in? Join us in "AI-Powered Fiction: Craft Amazing Novels with ChatGPT" and let's make your writing dreams come true with a little help from AI. Can't wait to see you there!

Animation and avatar creation using artificial intelligence (AI) are a huge development in the entertainment and art industry. This field combines art and technology in an amazing way, making it possible to create amazing virtual worlds and impressive characters. The process begins with creating sketches and designs for the characters, where their appearance and unique characteristics that distinguish them from others are determined. 3D graphics techniques are then used to model these characters in the finest detail, creating a realistic and tangible embodiment of them. When it comes to character movement, AI comes into play. Intelligent systems are programmed to animate the characters in a way that makes them appear alive and vibrant, where natural movements and facial expressions are accurately simulated. All these advanced technologies work to produce animated scenes that look realistic and arouse amazement and admiration among viewers. It is an exciting and complex process that requires great effort and high artistic and technical skills to achieve amazing results that satisfy expectations. This approach contributes to the development of the entertainment industry and opens up new horizons for creativity and artistic expression. In addition, AI technologies enable characters to interact with their environment in a dynamic and realistic way. Intelligent software can sense and intelligently adapt to motion, sound, and environmental interactions. This creates an exciting and interactive viewing experience for users, where they feel as if they are actually participating in the dazzling animated worlds. Artificial intelligence techniques enhance the realism of the scenario and make the characters appear real.