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Learn 10-601: Introduction to Machine Learning

UdemyBeginner

Welcome to the 10 Days of Prompt Engineering, Generative AI, and Data Science Course Get 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 XG Boost & 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 BREAKDOWN Introduction Meet 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 Engineering Learn about transformers, attention, and chain-of-thought prompting.Experiment with LM Studio to practice

Learn 10 FREE AI Courses for Absolute Beginners in 2025

UdemyBeginner

This 200+ day globally recognized, industry-focused bootcamp is your all-in-one training for mastering Artificial Intelligence, Data Science, Machine Learning (ML), Deep Learning (DL), and Generative AI (GenAI)  from beginner to expert level with simplicity and depth. Designed for aspiring data scientists, software engineers, AI professionals, and innovation leaders, this course offers a blend of foundational theory, programming practice, machine learning applications, and real-world project. The curriculum aligns with current global AI trends and industry hiring standards.Whether you're targeting top roles in global tech firms, launching an AI-powered startup, or aiming to build a strong data science portfolio this bootcamp ensures you stay ahead in the global AI race.Core Modules (SEO Keywords: Data Science, Python, AI, Machine Learning, Generative AI)Data Science Fundamentals Data Science Sessions Part 1 & 2 – Foundation of modern data science methodologies and approaches.Data Science vs Traditional Analysis – Comparing data science techniques with conventional statistical methods.Data Scientist Journey Parts 1 & 2 – Skills, roles, and global career pathways.Data Science Process Overview – End-to-end project lifecycle and workflows.Programming Essentials (Python & R for Data Science)Introduction to Python for Data Science – Syntax, structures, and data analysis workflows.Python Libraries: Numpy, Pandas, Matplotlib, Seaborn – Building blocks for data processing and visualization.Introduction to R – Fundamentals of R programming for statistics and machine learning.Data Structures and Functions – Hands-on practice in Python & R for real-world data operations.Data Collection & Preprocessing Methods of Data Collection – Surveys, A

Udemybeginner

This is an ambitious course. The goal here is simple: Only teach what you need to know for day 1 of your first data science job. No fluff, nothing out of context, no topics that are not relevant to real world applications. We will cover EVERY core topic and tool required for those new to data science: Python, R, SQL, Useful Math/Stats/Algorithms, Tableau, and Excel in depth. The course will cover skills that align with three different job types:- Data Analyst- General Data Scientist- Machine Learning Engineer You can expect to learn from first principles the foundational topics and tools used in practice today. We will avoid topics that are not useful or are simply too advanced when starting out. Your journey will be guided by the Data Science Road Map, a collection of the best resources gathered through years of experience by the instructor.In addition, we will survey every important technology required on the job including Git Hub, Kaggle, the basics of cloud, web development and docker. With over 200 videos, readings, and assignments, you can be sure you will be well prepared to join the data community.If you are just getting started or want to fill in some of your knowledge gaps this course is for you!

UdemyAdvanced

This Online Bootcamp is a compact and accelerated version of our 400-hour in-person master's program.It has four parts:- In Part 1, you will learn the keys to Artificial Intelligence and the new Generative AI, as well as its potential to revolutionize businesses, startups, and employment.- In Part 2, you will learn to build professional-level LLM Applications, the most potential applications of Generative AI. You will also learn how to build Advanced RAG LLM Apps, Multimodal LLM Apps, AI Agents, Multi-Agent LLM Apps, and how to manage LLM Ops.- In Part 3, you will learn how to build traditional and Gen AI apps without coding using Cursor AI and the new AI Coding Assistants. You will learn what are AI Coding Assistants like Cursor AI, Claude AI, v0, o1, Replit Agent, etc, and how to increase their performance by combining them with tools like the Replit platform, simplified backends like Firebase, Replicate AI, Stable Fusion, or Deepgram.- In Part 4, you will learn how to create SaaS applications without coding using Cursor AI. You’ll also see, through two high-level real-world examples, how Generative AI is transforming the SaaS (Software as a Service) model.By the end of this program, you will know how to do the following:AI AND BUSINESS Know the businesses that AI puts at risk of disappearing.Know the new opportunities created by AI for businesses.Design a plan to introduce AI into your company.Select an appropriate pilot project to introduce AI into your company.Form the first AI team in your company.Prepare your company's AI strategy.AI AND STARTUP Identify 100 opportunities to create AI startups.AI AND EMPLOYMENT Know the professions that AI puts at risk of disappearing.Know the new p

UdemyBeginner

Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.Welcome to TensorFlow 2.0!What an exciting time. It's been nearly 4 years since TensorFlow was released, and the library has evolved to its official second version.TensorFlow is Google's library for deep learning and artificial intelligence.Deep Learning has been responsible for some amazing achievements recently, such as:Generating beautiful, photo-realistic images of people and things that never existed (GANs)Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning)Self-driving cars (Computer Vision)Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)Even creating videos of people doing and saying things they never did (Deep Fakes - a potentially nefarious application of deep learning)TensorFlow is the world's most popular library for deep learning, and it's built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning.In other words, if you want to do deep learning, you gotta know TensorFlow.This course is for beginner-level students all the way up to expert-level students. How can this be?If you've just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts.Along the way, you will learn about

UdemyAdvanced

226 ChatGPT Prompts: A-Z ChatGPT Prompt Engineering Boot Camp Hey there, it's me, your next big career move. If you've ever thought, "How can I leverage the power of ChatGPT to elevate my game in my profession?", then this course is your answer. We're not just talking about a few tips here and there; this is the ultimate guide, the A-Z, the whole Bootcamp!Here's what you're getting:226+ ChatGPT Prompts tailored for various professions and life scenarios. Whether you're in logistics, HR, teaching, or even looking for a job, we've got you covered.Real-World Use Cases & Practice Exercises: Don't just learn, do. Apply what you learn in real-time, see the results, and iterate.Exclusive Access to Our Comprehensive ChatGPT Book: All the prompts we discuss? They're in there. A handy reference for whenever you need it.Stay Updated: This isn't a one-and-done deal. The course is updated with the latest from ChatGPT, including plugins, DALL·E 3, advanced analytics, and more.Diverse Categories: From e Commerce and content creation to health, fitness, and even travel. We've thought of everything, and then some.Why This Course?Look, the digital age is here, and it's not waiting for anyone. ChatGPT is revolutionizing how we work, communicate, and even learn. But here's the thing: knowledge without application is just trivia. This course ensures you apply what you learn, making you more efficient, effective, and, quite frankly, indispensable in your field.A Word from Your Instructor:I genuinely care about your growth. I'm not here to sell you a dream. I'm here to give you the tools to build that dream. This course? It's one

A comprehensive system for capturing, processing, enhancing, and monetizing 3D reconstructions using open-source tools and Python automation. Includes modules on 3D Python, Point Cloud Processor, and 3D Vision.

UdemyIntermediate

Solve Business Problems Using Data Science Practically. Learn To Build &amp; Deploy Artificial Intelligence, Machine Learning, Data Science , Auto Ml, Deep Learning, Natural Language Processing (NLP) Web Applications Projects With Python (Flask, Django, Heruko, Streamlit Cloud).How much does a Data Scientist make in the United States?The national average salary for a Data Scientist is US$1,20,718 per year in the United States, 2.8k salaries reported, updated on July 15, 2021 (source: glassdoor)Salaries by Company, Role, Average Base Salary in (USD)Facebook Data Scientist makes USD 1,36,000/yr. Analyzed from 1,014 salaries.Amazon Data Scientist makes USD 1,25,704/yr. Analyzed from 307 salaries.Apple Data Scientist makes USD 1,53,885/yr. Analyzed from 147 salaries.Google Data Scientist makes USD 1,48,316/yr. Analyzed from 252 salaries.Quora, Inc. Data Scientist makes USD 1,22,875/yr. Analyzed from 509 salaries.Oracle Data Scientist makes USD 1,48,396/yr. Analyzed from 458 salaries.IBM Data Scientist makes USD 1,32,662/yr. Analyzed from 388 salaries.Microsoft Data Scientist makes USD 1,33,810/yr. Analyzed from 205 salaries.Walmart Data Scientist makes USD 1,08,937/yr. Analyzed 187 salaries.Cisco Systems Data Scientist makes USD 1,57,228/yr. Analyzed from 184 salaries.Uber Data Scientist makes USD 1,43,661/yr. Analyzed from 151 salaries.Intel Corporation Data Scientist makes USD 1,25,930/yr. Analyzed from 131 salaries.Airbnb Data Scientist makes USD 1,80,569/yr. Analyzed from 122 salaries.Adobe Data Scientist makes USD 1,39,074/yr. Analyzed from 109 salaries.<

UdemyIntermediate

In This Course, Solve Business Problems Using Data Science Practically. Learn To Build &amp; Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).Data science can be defined as a blend of mathematics, business acumen, tools, algorithms, and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.In data science, one deals with both structured and unstructured data. The algorithms also involve predictive analytics. Thus, data science is all about the present and future. That is, finding out the trends based on historical data which can be useful for present decisions, and finding patterns that can be modeled and can be used for predictions to see what things may look like in the future.Data Science is an amalgamation of Statistics, Tools, and Business knowledge. So, it becomes imperative for a Data Scientist to have good knowledge and understanding of these.With the amount of data that is being generated and the evolution in the field of Analytics, Data Science has turned out to be a necessity for companies. To make the most out of their data, companies from all domains, be it Finance, Marketing, Retail, IT or Bank. All are looking for Data Scientists. This has led to a huge demand for Data Scientists all over the globe. With the kind of salary that a company has to offer and IBM is declaring it as the trending job of the 21st century, it is a lucrative job for many. This field is such that anyone from any background can make a career as a Data Scientist.In This Course, We Are Going To Work On 50 Real World Projects Listed Below:Project-1: Pan Card Tempering Detector App -Deploy On Heroku

AWSIntermediate

An article that delves into seven essential AWS services and architectural patterns that solutions architects need to know to successfully design and implement AI-powered solutions in the cloud.

Learn 99% of Beginners Don't Know the Basics of AI

Learn 99% Of People STILL Don't Know The Basics Of Prompting (ChatGPT, Gemini, Claude)

This Udacity course, developed by Google, provides a practical introduction to A/B testing. You will learn how to design and analyze A/B tests. The course covers topics such as metrics, sample size, and statistical significance.

DatacampIntermediate

This course focuses on A/B testing, a common application of hypothesis testing in the industry. You will learn how to design and analyze A/B tests using Python. The course covers topics such as sample size calculation, statistical power, and the interpretation of results.

Sharpen your skills for AI interviews by diving deep into neural networks, NLP, and transformer models. Master techniques like gradient descent, transfer learning, and model evaluation to stand out.

Prepare for Python coding interviews with data structures, algorithms, and problem-solving patterns.

CourseraBeginner

This course from the University of Pennsylvania provides a comprehensive introduction to causal inference, covering topics like potential outcomes, confounding, directed acyclic graphs (DA Gs), matching, and instrumental variables.

UdemyBeginner

Course Contents Deep Learning and revolutionized Artificial Intelligence and data science.&nbsp; Deep Learning teaches computers to process data in a way that is inspired by the human brain.This is complete and comprehensive course on deep learning. This course covers the theory and intuition behind deep learning models and then implementing all the deep learning models both in PyTorch and TensorFlow.Practical Oriented explanations Deep Learning Models with implementation both in PyTorch and TensorFlow.No need of any prerequisites. I will teach you everything from scratch.Job Oriented Structure Sections of the Course· Introduction of the Course· Introduction to Google Colab· Python Crash Course· Data Preprocessing· Regression Analysis· Logistic Regression· Introduction to Neural Networks and Deep Learning· Activation Functions· Loss Functions· Back Propagation· Neural Networks for Regression Analysis· Neural Networks for Classification· Dropout Regularization and Batch Normalization· Optimizers· Adding Custom Loss Function and Custom Layers to Neural Networks· Convolutional Neural Network (CNNs)· One Dimensional CNNs· Setting Early Stopping Criterion in CNNs· Recurrent Neural Network (RNNs)· Long Short-Term Memory (LSTMs) Network· Bidirectional LSTMs· Generative Adversarial Network (GANs)· DCGA Ns· Autoencoders· LSTMs Autoencoders· Variational Autoencoders· Neural Style Transfer· Transformers· Vision Transformer· Time Series Transformers. K-means Clustering. Principle Component Analysis.&nbsp; Deep Learning Models with implementation both in PyTorch and TensorFlow.

LinkedIn LearningAdvanced

For those with some machine learning experience, this course provides a deeper dive into deep learning with TensorFlow. It covers advanced topics like building custom neural networks, and working with text and sequence data.

This program focuses on AI-driven solutions, smart grid optimization, and data analytics for sustainable energy management, designed for engineers, data scientists, and energy professionals.

This advanced masterclass goes beyond foundational AI applications, empowering you to harness sophisticated artificial intelligence, including powerful topic modeling techniques like Latent Dirichlet Allocation (LDA) and Structural Topic Modeling (STM), to conduct systematic literature reviews with unparalleled depth and efficiency.

CourseraIntermediate

This specialization from the University of Colorado Boulder covers various aspects of business analytics, with a strong emphasis on statistical modeling and data-driven decision making.

An expert-level course covering advanced methods for causal discovery, effect estimation with high-dimensional data, and handling unobserved confounding.