Hey friend! Get ready to jump into the amazing world of artificial intelligence with my list of FREE AI courses to own 2024. Hang on tight because we’re smashing through barriers and delving into the latest and greatest in AI. No holding back, no price tags — just pure, unstoppable knowledge waiting for you to grab. Let’s change the game in how you see AI and make 2024 the year you conquer this tech wonderland!
ChatGPT Prompt Engineering for Developers
Get ready to rock the “ChatGPT Prompt Engineering for Developers” course! Dive into the world of using a beastly Large Language Model (LLM) via the OpenAI API to whip up applications that were once considered a headache — too expensive, too technical, or just plain undoable. Isa Fulford (OpenAI) and Andrew Ng (DeepLearning.AI) are your guides in this adventure. They’ll unravel the mysteries of LLMs, spill the beans on prompt engineering best practices, and flaunt the versatility of LLM APIs in tasks like summarizing, inferring, transforming text, and even expanding your email-writing game.
But that’s not all! You’ll be schooled in two ninja principles for crafting prompts that get results, learn the secret sauce for systematically engineering killer prompts, and cap it off by creating your own custom chatbot. And the best part? Dive into the examples they throw at you, play around in the Jupyter notebook environment, and get your hands dirty with prompt engineering. It’s a wild ride into the future of AI applications!
AI For Everyone
AI isn’t exclusive to engineers anymore. If you’re aiming to enhance your organization’s AI capabilities, this course is the one to recommend to everyone, especially those without a technical background.
Throughout this course, participants will:
- Gain an understanding of common AI terminology, including neural networks, machine learning, deep learning, and data science.
- Discern the realistic capabilities and limitations of AI.
- Identify opportunities to apply AI to challenges within their own organization.
- Experience the process of building machine learning and data science projects.
- Learn how to collaborate with an AI team and develop an AI strategy for their company.
- Navigate ethical and societal discussions surrounding AI.
While this course is designed to be accessible for non-technical individuals, it also offers valuable insights for engineers looking to grasp the business aspects of AI.
Learn Prompting
Get ready for an incredible learning experience — this place is like no other. It’s a thrilling adventure into the world of prompt engineering, and the best part? It won’t cost you a penny — completely free and open to everyone. Whether you’re a coding wizard or just starting out, you’re more than welcome there!
access the course from here
Introduction to AI By the University of Helsinki
Explore the Elements of AI, a captivating series of free online courses meticulously crafted by MinnaLearn and the University of Helsinki. These courses aim to empower a diverse audience to delve into the world of AI, understanding its capabilities, limitations, and the process of initiating AI methods. Engage in a mix of theory and practical exercises, enabling you to learn and grow at your own pace. This learning adventure is yours to discover!
Deep Learning Specialization
Discover the world of AI with the Deep Learning Specialization, a foundational program meticulously designed to deepen your understanding of deep learning, its challenges, and its impactful role in AI technology. This specialized program readies you to actively contribute to the forefront of AI developments.
Throughout the course, you’ll construct and train diverse neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, LSTMs, Transformers, and refine them using advanced strategies like Dropout, BatchNorm, Xavier/He initialization, and more. Gain hands-on experience with Python and TensorFlow as you tackle real-world challenges such as speech recognition, music synthesis, chatbots, machine translation, natural language processing, and more. This specialization not only equips you with practical skills but also offers career advice from deep learning experts in both industry and academia.
Harvard’s Data Science: Machine Learning
One of the most widely adopted approaches in data science is derived from machine learning, setting itself apart by constructing prediction algorithms based on data. Unlike other computer-guided decision processes, machine learning relies on building algorithms that predict outcomes using available data. This versatile methodology has given rise to widely used applications, from the postal service’s handwriting readers to speech recognition, movie recommendation systems, and spam detectors.
In this course, a key component of the Professional Certificate Program in Data Science, participants will delve into popular machine learning algorithms, principal component analysis, and regularization, all while constructing a movie recommendation system. The journey encompasses understanding training data, unraveling the secrets of discovering predictive relationships within a dataset, and gaining insights into training algorithms for predicting outcomes in future datasets. Along the way, participants will also grasp crucial concepts such as overtraining and strategies like cross-validation to steer clear of potential pitfalls. These skills form the bedrock of machine learning, equipping participants with the tools to navigate and excel in this dynamic field.
Stanford CS224N
In this insightful YouTube video, viewers will explore various facets of NLP and deep learning, gaining a profound understanding of essential concepts. The video starts with an overview of the course, followed by a captivating exploration into human language and word meaning. The spotlight then shifts to the Word2vec algorithm, uncovering its intricacies and diving into the gradients of its objective function.
Optimization basics take center stage, providing a foundational understanding in just 5 minutes, paving the way for a quick yet comprehensive examination of word vectors. Brace yourself for a revelation — the surprising realization that word meaning can be effectively represented by a large vector of real numbers.
What can viewers expect to learn in this course? The foundations of modern, effective deep learning methods tailored for NLP. Starting with the basics, participants will progress through key NLP methods such as recurrent networks, attention mechanisms, and transformers. Gain a holistic understanding of human languages, exploring the challenges in comprehending and generating them. And that’s not all — this course empowers participants to build systems, using Pytorch, to tackle major NLP problems like word meaning, dependency parsing, machine translation, and question answering. Ready to unlock the secrets of NLP and deep learning? Hit play!
