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Becoming Data Science professional (Data Scientist) is a long journey and need guidance from seasoned Data Science professional (Chief Data Scientist). We are trying to manage the journey such a way that you learn right skills and in the right way. The whole concepts of the course are to make you ready for Data Science projects, mainly in Machine learning and AI projects. You will learn 1. Foundation of Machine learning 2. Supervised Machine learning - Regression 3. Supervised Machine learning - Classifications 4. Unsupervised Machine learning (Clustering, KNN, PCA) 5. Text Analytics 6. Time Series 7. RShiny

Welcome to the comprehensive course on building chatbots with OpenAI! Chatbots have revolutionized the way businesses and individuals interact with users, providing efficient and personalized experiences. In this course, we will take you on a step-by-step journey, starting from the basic concepts of APIs and testing OpenAI APIs using tools like Postman, to creating fully functional chatbots using HTML, JavaScript, and CSS. By the end of this course, you will possess the skills and knowledge to develop and deploy your own chatbot. The course begins with an introduction to APIs and how they form the backbone of chatbot development. You will learn how to utilize Postman to test OpenAI APIs and configure the environment for seamless integration. Through hands-on exercises, you will gain proficiency in setting up workspaces, collections, and API keys, enabling you to interact with OpenAI models effectively. As the course progresses, you will dive into the world of chatbot development, exploring the different models provided by OpenAI, such as GPT-3.5 Turbo, and understanding how to leverage them to create engaging conversational experiences. You will learn how to define user and system rules, customize messages, and guide the behavior of your chatbot. Furthermore, you will discover how to integrate your chatbot into web pages, enabling users to interact with it seamlessly. With the use of HTML, JavaScript, and CSS, you will have the power to shape the user interface and enhance the overall user experience. The course will guide you through the process of uploading your chatbot to live servers, allowing you to share your creation with the world. By the end of the course, you will have gained the confidence to build chatbots that can understand and respond to user queries, provide recommendations, and even simulate human-like conversations. Join us on this immersive journey as we unlock the potential of chatbot development with OpenAI. Get ready to harness the power of artificial intelligence and create chatbots that transform the way we engage with technology. Enroll now and embark on an exciting adventure into the world of chatbot creation!

Machine learning is a subset of artificial intelligence that is at the forefront of digital transformation in the world. Thanks to machine learning, it is now possible to detect diseases, know the defaulters of a loan and know the future sales of a product. All these information can be had proactively and not as an after the fact scenario. Machine learning and artificial intelligence-based roles are in great demand in the job market and such roles offer a higher salary than traditional programming roles. This course covers the concepts of machine learning as well as the application of these concepts using case studies and examples, along with a walk through of the python codes. Python programming is also covered for the benefit of those who are new to python and those who want to refresh some of the topics in python. The following algorithms are covered in detail: - Simple and multiple linear regression - Logistic regression - Decision tree, Random forest and XG boost - Unsupervised algorithms - Cluster (kNN based) and Hierarchical. Learners will also understand how to develop the above machine learning in a cloud environment. They will learn not just to code in cloud but also to access the data stored in cloud. This will be particularly helpful to learners since many organizations are adopting cloud at a fast pace. A key aspect of the course is the coverage of Exploratory Data Analysis (EDA). EDA covers the set of activities that you do before you start the ML project. Lastly, how to pursue a machine learning project has been covered. This course is taught by an industry veteran, who brings his vast experiences and practical perspectives into the program.

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Our Beginners Guide to Generative AI is a great starting point for beginners or creators that want to start to get their feet wet in the world of generative AI. 2023 has been a breakout year for CHATGPT-4 and Microsoft New Bing, but the power of Artificial Intelligence goes beyond text responses. Generative Artificial Intelligence (AI) is one of cutting edge applications from Images, Music, Popular voice covers of Donald Trump, and Video. Many people have heard of CHATGPT4, which is primarily focused on providing text responses back to uses. Our beginner's course will cover other platforms such as Adobe Firefly (Beta), Midjourney, and Dalle to provide you the landscape and practical knowledge in this field. Adobe Firefly also provides additional applications like Text Effects and Vector colours and creatives will get early exposure to these beta applications. Adobe Photoshop Beta Generative Fill has been released with AI capabilities covered in this course. We will also teach you how to get started using AI to convert your favourite songs to popular AI voices like Joe Biden, Donald Trump, Drake & more using Voicify. We also also get you started creating your own music beats for use in your social media using the platform soundful. The end game points to text to Video. An in our text to video section we will give you an introduction to the text to Video application of Synthesia where you can create videos with AI avatars in multiple languages and export/import your videos into powerpoint slides and vice versa. We will even show you show to edit these video downloads in Final Cut Pro and Adobe Premiere Pro

Want to be a game developer? Want to learn artificial intelligence? Want to build mobile games? If you answered yes, this course is for you! Funded by a #1 Kickstarter Project by Mammoth Interactive Welcome to Mammoth Interactive's Complete Unity® Masterclass: Build 2D & 3D AI Games with Glauco Pires. You will learn how to make 3 complete games in Unity and C#! In the first part of this course, you will learn to use the A* algorithm to make a 2D game in Unity 2017.3. Learn to code for game development in Unity C#. Make a game that uses artificial intelligence. Make a path-finding algorithm. Use the A* algorithm to make a 2D game in Unity. A Super Tank on a maze will find the best way to go to a point you click. The tank will collect objects along its path. The A is the base algorithm for path finding. A is artificial intelligence that will find a path. This algorithm has existed for decades. You can use A* in many different platforms, programming languages and more. A* is also important to avoid dangers like a cliff while getting to a destination. As well - suppose a game's level has two paths. You can program your artificial intelligence player to think on its own. It can choose a better path to avoid monsters and other obstacles. Included in this course is material for beginners to get comfortable with the interfaces. Please note that we reuse this content in similar courses because it is introductory material. You can find some material in this course in the following related courses: Learn artificial intelligence by building games and apps ​The Complete 2D Unity & AI for Games with Algorithms Course Learn Unity AI by Making a Tank Game​! Make a Starship Unity Game Powered by Artificial Intelligence The 2D, 3D & AI Games Frontier: NavMesh, Unity & Illustrator Make a Ninja Survival game for mobile in Unity and Blender Practical Unity Developer Academy: Make Fully Featured Games A to Z Unity Development: Code in C# and Make Low Poly Art C# & Image Processing Masterclass: Make Mobile Games & Apps Build 22 Games in GameMaker Studio, C# Unity® & Blender C# Masterclass: Make RPG & Mobile Games in Unity & Blender In the second part of this course, you will program a spaceship in a three-dimensional game. With artificial intelligence your ship character will learn to explore a planet. The ship will travel around craters, rocks, aliens and buildings in a 3D world. Use a navigation mesh to add pathfinding logic to your game. Code in C#. Learn cutting-edge tools that will put you ahead of other developers. In the third part of this course, you will learn how to build a Ninja game for mobile using Unity® and Blender. The Complete Unity® Masterclass: Build 2D & 3D AI Games is unique because we make both the code and the art for the game from scratch. Integrate art from Blender into Unity®. Build video game levels. UV map and unwrap 3D models. Create your own materials. And more! You will design the game and its functionality in Unity®. Don't worry if you've never coded before. You will start simple and add more to the game as the course goes on. Why Unity®? Unity® is one of the most popular platforms in game development. You can use Unity® to build 2D and 3D games. Unity® is cross-platform, which means it is easy to use with other platforms. You create game art for the game in Blender. You will build all the art assets for the game. You will learn to integrate your art from Blender into Unity®. Why Blender? Blender, like Unity®, is a popular production suite that is free to download. Blender is a revolutionary tool for making 3D art digitally. With Blender, you can make art assets for games, like we do in this epic Mammoth Interactive course. Enroll Now for Lifetime Access

Artificial Intelligence, Deep Learning, Machine learning and Data Science are buzz words that you would hear quite often these days. These area provide good number of job opportunities and it very much essential that you understand the fundamentals concepts of these when facing an interview. This course aims to feed you with confidence to face a coding interview on Machine Learning and Deep Learning. We shall walk over 50+ interview questions with hands-on code and prepare you for the same. All of the code is written in Python and will focus to explain the concepts from scratch. - Do you know, About half a million job openings are available across the globe. Data Science and ML engineer are the job roles with most openings - Harvard Business Review has stated that "Data Science" as most attractive job of the 21st century. - last but not the least The Salary bar in this domain is also quite high than regular IT professionals. In-fact, The demand for these niche skills are 10 times more than the number of graduates passing out of the college. Given so much of background on need to adopt this skill, would you not take a shot at it ..? I would recommend that, Whichever is your career path just club it up with AI and then accelerate . So why wait? Lets get Started.

Introduction to Generative AI: A clear understanding of GenAI technology, its capabilities, and how it differs from traditional AI. Data as the Fuel: The role of data in GenAI. Learn how data quality and management impact the success of GenAI projects. GenAI Use Cases: Discover a wide range of real-world applications of GenAI across various sectors. Demo of GenAI Tools: Get a hands-on feel for GenAI through guided demonstrations of user-friendly no-code AI tools. Past, Future, and Adaptation: Explore the historical development of GenAI, its future trajectory, and how businesses can adapt it.

Knowledge of "soft skills" or " people skills " is increasingly in the spotlight and recognized as critical to success - which is why at IBM we call them "hard skills " and categorize them as "hard skills ." A study conducted by Harvard University, the Carnegie Foundation and the Stanford Research Center found that 85% of job success comes from strong soft and people skills, while only 15% of job success comes from technical skills and knowledge. (hard skills). This specialization aims to help you develop these powerful people skills and soft skills and behaviors that include: creating and delivering impressive presentations; work professionally, providing quality work and experience effective collaboration with teams; productive and effective communication; overcoming difficulties, solving problems and implementing solutions. The program consists of 5 short courses that you can take in any order, followed by a final assessment course. Upon completion of this specialization, you will have acquired knowledge and demonstrated understanding of these critical skills. Anyone can take this specialization , regardless of your age and work experience . It is especially useful for those just starting out or in the early stages of their career. There are no prerequisites for the course and this course can be taken either through the Coursera mobile app or through a web browser on a laptop/desktop/tablet/mobile device. Applied Learning Project Courses in this specialization include a variety of real-life examples and scenarios to help you develop critical people and soft skills. The final assessment also consists of mini-cases. Not only will this case study approach help you learn how to apply these fundamental skills, mastering them will give you an advantage in your career by better understanding the skills you need to succeed in your professional and personal life.

Generative AI uses predictive algorithms to process incoming requests and queries, synthesize data and create novel responses. Generative AI can produce written text, image, audio, and video responses. When used effectively, generative AI can help marketers analyze trends, develop content, and curate messaging and channel strategies. Generative AI tools are evolving rapidly, so marketers should understand their strengths and limitations while integrating AI into their daily workflows. AI isn’t meant to replace the critical thinking and creativity that marketers bring to their roles. However, it can support daily marketing tasks by analyzing data and synthesizing information to distill trends and core themes. It’s also a powerful tool to help you spark creativity and can be used for brainstorming, iterating concepts, and drafting copy for marketing materials. One of the most effective ways to use AI is to help yourself automate tasks and workflows, so you can save your time and energy for the marketing tasks that require a skilled marketer’s touch.

One monumental stride in the realm of generative AI is the creation of large language models, such as GPT (Generative Pre-trained Transformer) and DALL-E. GPT is capable of creating coherent and contextually relevant textual responses to an assortment of prompts. It has been instrumental in the genesis of AI chatbots like ChatGPT, which possesses the prowess to answer an inexhaustible array of queries, as well as generate content spanning computer code, essays, poetry and beyond. DALL-E, on the other hand, is adept at crafting images from textual portrayals or writing text captions for images. While AI models are staggeringly powerful, they are also literal and are heavily contingent on the quality of input they receive. A nuanced alteration in prompt phrasing can trigger dramatically different outputs. Moreover, language models lack innate comprehension or common sense, so prompt engineering is shepherding them to yield meaningful and contextually accurate responses. Prompt engineering allows product managers to tailor the behavior and output of AI models to specific use cases or applications. They can experiment with different prompt variations, fine-tuning the language, structure, and specific details to elicit the desired response.

This six-week course provides a comprehensive immersion and smooth transition from Python, AI, ML, and DL to cutting-edge GenAI, essential for careers in science, engineering, management, and beyond. It offers vital skills to innovate and create solutions with AI technology, enhancing job market preparedness and competitiveness for students, faculties, and professionals alike. The course do not assume any pre-requisite knowledge of Python or AI or ML, although such previous exposure would be definitely helpful. Learning Outcome: At the end of this course the students will be able to • utilize basic concepts and terminology related to AI, ML, DL and GenAI for applications in science, engineering, and management • explore various deep learning and generative AI architectures including attention mechanisms • build real-world projects applying deep learning and generative AI models • develop and fine-tune Large Language Models (LLMs) for a specific application • gain insights into ethical considerations and best practices in AI development