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Today, Artificial Intelligence and Machine Learning are becoming essential skills. These technologies are all around us — from unlocking our phones with face recognition to getting suggestions for videos, products, or even routes when we travel. AI is being used in almost every field to make processes faster, smarter, and more efficient. Companies use AI to improve customer service and decision-making. In hospitals, AI helps doctors detect diseases early. In schools, it helps personalize learning for students. Even in farming, AI helps increase crop production and reduce waste.
As more industries move toward automation and data-driven decisions, learning about AI and ML gives you an edge. Whether you're a student, a job seeker, or someone simply curious about new technology, now is the perfect time to start.
1. Deep Learning Prerequisites: The Numpy Stack in Python V2
Numpy, Scipy, Pandas, and Matplotlib: prep for deep learning, machine learning, and artificial intelligence
- Basic operations in Numpy, Scipy, Pandas, and Matplotlib
- Vector, Matrix, and Tensor manipulation
- Visualizing data
- Reading, writing, and manipulating DataFrames
2. Introduction to AIOps
Harnessing Artificial Intelligence for Smarter IT Operations" "Automating IT Operations with AI and Machine Learning"
- Comprehensive Understanding of AIOps Concepts: How AI transform IT operations using automation, predictive analytics, and real-time anomaly detection.
- Proficiency in AIOps Tools: Gain hands-on experience with leading AIOps platforms to streamline IT operations, enhance performance, and minimize downtime.
- Ability to Implement AIOps Solutions: Integrate AIOps into IT environments for automated monitoring, root cause analysis, and proactive incident management.
- Enhanced Decision-Making Skills: Confidently use AI insights to drive decisions, optimize resources, and enhance the reliability and scalability of IT systems.
3. Fundamentals of Machine Learning Regression
Master the Fundamentals of Regression Techniques in Machine Learning: SciKit Learn and Pandas Essentials
- Grasp the fundamental concepts of regression and its importance in predicting continuous outcomes
- Implement and evaluate models to solve real-world problems
- Learn data preprocessing techniques, including data cleaning and transformations using pandas
- Learn to evaluate regression models using metrics such as R² Score to assess model accuracy and performance.
- Understand the importance of splitting data into training and testing sets to validate model performance
- Learn how to build and implement linear regression models using SciKit Learn to predict target variables based on input features.
- Understand the key differences between classification and regression tasks, including their objectives and different real world applications
- Learn to build and implement decision tree models for regression using SciKit-Learn
- ain knowledge of SVMs and how to apply them for regression tasks, including the concepts of hyperplanes and margins.
4. Learn basics about A.I. (Artificial Intelligence)
Explore history, development and advances in artificial intelligence and more recently in machine learning
- What is Artificial Intelligence?
- How artificial intelligence developed over the past?
- What types of artificial intelligence exist?
- Where AI is already applied and where it will be applied in future?
- How AI will change the way we work? What changes in job market can be expected from penetration of AI?
5. Using AI To Code Machine Learning Apps
Using AI And Machine Learning To Enhance Your Coding Skills & Efficiently Build ML Tools
- Explain the benefits and challenges of using AI to code machine learning apps
- Identify and select the best AI tools and platforms for your use case and budget
- Use AI to generate machine learning code for various tasks and functions, such as data preprocessing, model building, model training, etc.
- Use AI to edit and optimize machine learning code for various aspects and criteria, such as performance, accuracy, efficiency, etc.
- Use AI to deploy and test machine learning code on various platforms and devices, such as web, mobile, cloud, etc.
- Use AI to improve and maintain machine learning code by adding new features, fixing bugs, updating data, etc.
6. Machine Learning vs Deep Learning : Basics to Applications
Machine Learning , Deep Learning. Artificial Neural Networks, Image Analysis,
- The students will be able to distinguish between the pros and cons of supervised and unsupervised machine learning techniques
- The students will be able to apply supervised machine learning algorithms for practical applications
- The students will be able to distinguish between the supervised and unsupervised artificial neural networks
- The students will be able to develop modified artificial neural network algorithms for imaging applications
Learn the core principles of modern Artificial Intelligence and how it's impacting your life. Without coding or math!
artificial intelligence
machine learning
natural language processing
computer vision
face recognition
data science
recommender systems
8. Artificial Neural Network for Regression
Build an ANN Regression model to predict the electrical energy output of a Combined Cycle Power Plant
- How to implement an Artificial Neural Network in Python
- How to do Regression
- How to use Google Colab
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9. Principles of Machine Learning
Explore core ML concepts and algorithms like supervised learning, concept learning, Find-S, and Candidate Elimination.
Understand well-posed learning problems and key components of a machine learning system.
Analyze concept learning as a search problem and apply it to hypothesis spaces.
Implement and evaluate the Find-S algorithm for concept learning tasks.
Apply the Candidate Elimination algorithm to refine hypothesis spaces based on training data.
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10. The Ultimate Beginners Guide to Machine Learning
Learn everything you need to know to start your studies in Machine Learning! Theory and practice!
- Learn an initial theoretical basis on some machine learning algorithms
- Implement simple projects using Orange tool for machine learning tasks such as classification, regression, clustering and association
- Learn machine learning without knowing a single line of computer programming
- Use Orange visual tool to create, analyze and test algorithms
11. Synthetic Data in Machine Learning
Synthetic Data in Machine Learning: From Theory to Practice
Explain the concept of synthetic data and its importance in machine learning applications, including its relevance to enterprise data strategies.
Identify and describe key techniques for generating synthetic data, including statistical methods and generative AI approaches like GANs and VAEs.
Evaluate the quality of synthetic data and recognize potential biases, ensuring the data is suitable for machine learning tasks
Apply synthetic data in a machine learning workflow, including training a model and comparing results between original and synthetic datasets.
12. Artificial Intelligence for Brand Protection Professionals
Understand the Convergence of AI and Intellectual Property
- Recall basic Artificial Intelligence (AI) concepts
- Describe the threat AI poses to intellectual property
- Describe the opportunities for AI to bolster brand protection efforts
- Identify resources to help your brand incorporate AI into your brand protection toolkit
13. AI in Agriculture: Practical Introductory Course
A Beginner’s Guide to AI Tools for Modern Agriculture
- Understand what artificial intelligence (AI) is and how it can help in farming.
- Learn the good and bad sides of using AI in agriculture.
- See real examples of how AI is used in agriculture.
- Learn about the main components of any AI system, including, agricultural one.
14. AI for Business and Personal Productivity: A Practical Guide
Master ChatGPT and Claude to 10x Your Output: Real-World Scenarios, Step-by-Step Workflows and Best Practices
- Productivity: Step-by-step, how AI can increase your productivity by 10x.
- Prompts: Everything you need to know about prompt engineering in 11 minutes and 58 seconds.
- Tools: Discover the only 2 AI tools you really need to be productive.
- Scenarios: Real-world, practical examples of using AI in your daily workflow.
- Data-Fu: Turn mountains of information into actionable insights in minutes, not hours.
- 1000X Speed: Consume hour-long videos in 60 seconds or less with AI-powered summaries.
- AI-Powered Inbox Zero: Process your email inbox 5x faster.
15. Planning with Artificial Intelligence
A Practical Approach to AI-Based Planning Methods
- Understand and apply machine learning techniques such as Linear Regression and Support Vector Machines (SVM) to solve real-world classification and regression p
- Explain the architecture and functionality of Expert Systems, and analyze their role in knowledge-based decision-making processes.
- Analyze and implement problem-solving strategies in AI, including Means-End Analysis and Goal Stack Planning, for automated reasoning and goal achievement.
- Demonstrate problem representation and planning using classical AI methods, with specific emphasis on structured problems like the Block World Problem.
- Evaluate different AI planning techniques and apply them in deterministic and goal-driven environments for intelligent agent design.
- Integrate concepts from machine learning and AI planning to build hybrid intelligent systems capable of learning from data and planning actions to achieve goals
16. Machine Learning : Solving Regression using Gradient Descent
Learn Regression & Gradient Descent Easily | Linear & Polynomial Regression | Machine Learning for Beginners |
- Learn regression & gradient descent like you're explaining it to a High school kid (but way more fun!).
- Cost functions sound scary? Not here! We make them as easy as splitting a pizza.
- Multilinear & polynomial regression—fancy words, simple concepts. We break it down like a dance routine!
- Machine Learning without headaches! No PhD required, just bring your curiosity (and maybe a coffee).
ChatGPT, Midjourney, Firefly, Bard, DALL-E, AI Crash Course
Learn AI Tools in just 15 minutes. Start using ChatGPT, Midjourney, Google Bard, Adobe Firefly and DALL-E today!
- Start using AI Tools Today! Learn ChatGPT, Midjourney, Google Bard, and DALL-E with quick & practical crash courses.
- AI-Powered Content Creation: Discover how to use ChatGPT & Google Bard to generate a variety of creative content, from blog posts to marketing materials.
- AI for Visual Creativity: Use Midjourney & Dall-E to generate photorealistic images, illustrations, and digital art in any style.
- Hands-On Experience: Apply what you've learned through interactive activities that simulate real-world scenarios, gaining practical experience with AI tools
- Stay Current: Grasp the trajectory of AI and machine learning trends, preparing you for future developments in these rapidly evolving fields.
- ChatGPT: Learn how to use ChatGPT to generate & edit any kind of text from articles, essays, video scripts, social media posts, emails, and more
- Midjourney: Learn how to create AI generated art, images, and photos from any idea you have
- Google Bard: Learn how to use ChatGPT to generate & edit any kind of text from articles, essays, video scripts, social media posts, emails, and more
- DALL-E: Learn how to create AI generated art, images, and photos from any idea you have
Machine Learning for Research
Learn about machine learning and its powerful applications in scientific research!
- Learn when it is appropriate to apply machine learning to scientific research
- Learn how supervised and unsupervised machine learning algorithms work
- How to take raw data and apply machine learning to develop conclusions
- How to conduct your own research project using machine learning
WEKA - Data Mining with Open Source Machine Learning Tool
WEKA tool for data preparation, classification, regression, clustering, association rules mining, and visualization
- Students can learn WEKA tool for data pre-processing, classification, regression, clustering, association rules, and visualization
Machine Learning: KNeighborsClassifier and Math Behind It
Master the K Nearest Neighbors (KNN) Algorithm and Uncover the Mathematical Foundations of Machine Learning
- Understand the fundamentals of machine learning and its applications.
- Gain an in-depth understanding of the K Nearest Neighbors (KNN) algorithm.
- Learn the mathematical concepts behind KNN, including distance metrics and the k-nearest neighbors approach.
- Explore the Iris flower dataset and understand its structure and features.
- Implement the KNN algorithm using scikit-learn's KNeighborsClassifier.
- Split a dataset into training and testing sets for model evaluation.
- Perform hyperparameter tuning using GridSearchCV to find the best combination of hyperparameters for the KNN model.
- Evaluate the performance of the KNN model using accuracy metrics such as accuracy score and classification report.
- Visualize the classification report to gain insights into the model's performance for each class.
- Understand the concept of feature importance and its relevance in machine learning models.
Introduction to Machine Learning in PHP
Learn to Build Different Machine Learning Models Easily
- You Will Learn how to implement some of the most common machine learning algorithms in PHP
- You will Learn about the some of the common algorithms like classification, regression, clustering
- You will learn about Supervised and Unsupervised learning
- You will NOT learn the details and mathmatics of each algorithm. Our focus is mainly on implementing them in PHP
- You will Learn about the steps to build a machine learning model
- You will Learn how to divide your data to training set and test set
- You will Learn how to train your machine learning model
- You will Learn how to make prdictions
- You will learn about the persistency of your model
Machine Learning for MBA and business school students
Learn about neural networks and decision trees and their applications to business problems.
- You will be able to describe the growth of the AI industry
- How to create a simple decision tree
- How to create a simple neural network
- How to apply machine learning to a wide variety of business problems
Mastering Machine Learning: A Guide to Research & Publishing
Create a research project using Machine Learning and Data Science for AP Research, publication, or passion projects.
- Develop a Personalized Research Blueprint
- Understand the Fundamentals of Machine Learning
- Apply Machine Learning Techniques to Data Analysis
- Implement Machine Learning Models Using TensorFlow
- Analyze and Visualize Data with Pandas
- Enhance Research Presentation Skills
- Submit a High-Quality AP Research Project
- Prepare and Submit Research for AP and Publication
- Apply Best Practices in Research and Publishing
Master ChatGPT: Build AI Assistants That Know Your Business
Learn to Build Your Very Own Custom AI Assistant That Writes, Thinks, and Responds Like You Would
- Build your own AI assistant using ChatGPT for real business tasks
- Use the ChatGPT interface and tools with confidence
- Understand what ChatGPT can and can't do, and how to work with it effectively
- Learn prompt engineering skills like step-by-step prompting and prompt chains
- Teach ChatGPT to match your brand voice and writing style
- Guide your AI assistant to choose and apply the right messaging framework for your audience
- Create core messaging assets like value propositions, elevator pitches, and messaging pillars
- Use your AI assistant to plan marketing campaigns, including themes, channels, and timelines
- Write landing pages and other campaign materials with the help of your AI assistant
- Create email sequences for different stages of your lead nurturing process
- Write ad copy for platforms like Google and LinkedIn, including A/B test variations
- Become more confident when you talk about or learn about AI
Artificial Intelligence Markup Language (AIML)
Create your own chatbots using the world's most popular chatbot language.
- How to use AIML (Artificial Intelligence Markup Language) to create your own chatbot
Mastering Machine Learning: Course-1
Taking First Step Towards Machine Learning
- Machine Learning
- Python
- Regression
- Classification
- Unsupervised Machine Learning
Artificial Intelligence (AI)
Learn Artificial Intelligence (AI), LLM, Prompt Engineering, ChatGPT, API and More —No Experience Needed!
- Explain the basics of Artificial Intelligence and its core concepts
- Describe how Natural Language Processing (NLP) powers modern AI tools
- Understand what large language models (LLMs) are and how they function
- Identify common use cases and fields for LLMs
- Apply prompt engineering techniques to get better results from AI tools
- Effectively use and compare all-in-one AI platforms
- Understand and use Application Programming Interfaces (APIs) for AI
- Work with API keys and manage tokens securely
- Integrate AI tools into real-world projects
- Gain practical, hands-on experience with leading AI solutions
Google Gemini AI with Python API - Quick Start
Learn how to leverage Google's powerful new Gemini AI model in just two hours!
- Understand Gemini AI Fundamentals: Grasp core principles, architecture, and applications of Large Language Models.
- Learn Text Generation: Acquire skills for generating coherent, contextually relevant AI text with nuanced tone and style.
- Comprehend Chat Models: Gain in-depth knowledge of chat model mechanics and learn customization techniques.
- Discover Configuration Optimization: Uncover and master critical Gemini AI configuration parameters for optimal performance.
- Identify Multimodal Integration: Recognize methods for integrating and analyzing visual and textual data using Gemini Vision.
- Create Vector Embeddings: Develop solutions using vector embeddings to capture semantic relationships in data.
- Explore RAG: Delve into Retrieval Augmented Generation, understanding how to dynamically incorporate external knowledge.
- Build AI Applications: Combine skills to design, develop, and deploy innovative AI applications using Gemini AI Python API.
AI-900 - Microsoft Azure AI Fundamentals
Master Microsoft Azure AI – Learn ML, NLP, Computer Vision & Responsible AI for Certification & Career Growth
- Understand AI Fundamentals
- Explore Azure AI Services
- Develop AI Solutions
- Prepare for AI-900 Certification
Smart ChatGPT Productivity Hacks for Business Professionals
Discover quick AI-powered techniques and smart prompts to streamline your tasks and save time at work!
- Understand how to use ChatGPT to streamline daily tasks and enhance business efficiency.
- Develop the ability to craft effective AI prompts that yield accurate and useful results for various business scenarios.
- Master the differences between ChatGPT and Gemini, and learn when and how to use each tool to maximize productivity.
- Implement AI strategies for task management, content creation, and automation, saving time and reducing manual work.
Artificial Intelligence for Healthcare -Prompt Engineering
Unlock the Power of AI to Streamline Healthcare Practices, Improve Patient Care, and Boost Efficiency
- Understand the fundamentals of prompt engineering and its significance in the healthcare domain.
- Learn how to communicate effectively with AI tools like ChatGPT, Claude, and Gemini in clinical and administrative settings.
- Gain the ability to craft well-structured prompts to receive accurate and relevant AI-generated responses
- Identify and apply the core components of an effective prompt: clarity, specificity, context, and assigned persona
- Differentiate between instructional, creative, and analytical prompts used in healthcare environments.
- Develop prompts for clinical documentation, patient education, and treatment comparison tasks.
- Explore real-world healthcare use cases where AI prompt engineering enhances decision-making and productivity.
- Build confidence in using AI tools responsibly and ethically as a modern healthcare professional.
Leadership 4.0 5 Day Challenge to Build Future Ready Leader
Discover the mindset, tools, and strategies to lead team and business in the age of AI and transformation.
- Measure what truly matters in your leadership
- Break free from outdated leadership mindsets
- Discover your personal leadership identity
- Build unstoppable self-leadership and discipline
- Craft your first AI-powered leadership strategy
- Drive transformation with clarity and confidence
- Lead high-performing teams through uncertainty
- Turn leadership insights into real-time action
- Future-proof your decision-making approach
- Unlock momentum with a 5-day sprint system
Tasting Machine Learning with Minitab Predictive Analytics
Minitab Machine Learning Preview: A Bite-Sized Look at Predictive Analytics. Regression, Classification
- Understand the concept of regression analysis and its applications in predictive modeling.
- Understand the concepts of overfitting and underfitting.
- Learn how to build a regression tree using Minitab.
- Learn how to set up a binary logistic regression model using Minitab.
- Practice building a classification tree and using it for prediction using Minitab.
Minimum Viable Programming for Maximizing AI
Learn how to get 1000x more out of Artificial Intelligence tools with just a LITTLE coding knowledge
- How to Maximize AI With Minimum Needed Programming Skills
- How to Use Programming to 1000x Your Ability to Leverage Artificial Intelligence
- The Minimum Viable Programming Needed for Maximizing Artificial Intelligence
- An Accelerated "Follow Along & Learn" To Program With Only The Necessary Skills Needed
How Smart People Use AI to Think, Lead, and Grow
Use ChatGPT for strategic thinking, leadership, growth, clarity, and personal performance.
- Use ChatGPT as a thinking partner for daily tasks
- Build clarity and confidence using AI in work and life
- Create a personal AI habit for growth and reflection
- Apply simple prompts to solve real-world challenges
Make Teaching Easier with Artificial Intelligence (Chat GPT)
The personal teaching assistant you've always wanted is now here. Learn how to use Chat GPT to enhance student outcomes.
- Learn different types of AI and how to use them as a teacher
- Save you time each week on administrative tasks
- Plan for the implications of Chat GPT on student assessment
- Increase your creativity and professional writing ability as a teacher
Python For Beginners
This course specifically created for Data Science / AI / ML / DL. It covers BASICS PYTHON ONLY
- Acquire the prerequisite Python skills to move into specific branches - Data Science(Machine Learning/Deep Learning) , Big Data , Automation Testing, Web development etc..
- Have the skills and understanding of Python to confidently apply for Python programming jobs.
Amazing AI: Reverse Image Search
Apply your Deep Learning skills and create your own end-to-end Image Search engine!
- What are Reverse Image Search engines
- How to build your AI based Reverse Image Search engine
- How to create simple web based interface for your Deep learning models using the Python framework Flask
- Coding a Convolutional Neural Network (CNN) from scratch in Tensorflow 1.10.0
- Using the Python framework Flask to serve a Deep Learning model in production
- How to create an End-to-End pipeline for any Deep Learning model using Tensorflow
Practical Introduction to ChatGPT - AI Academy
Master ChatGPT: From Novice to AI Power-user in 6 Lessons with Harvard AI Professor Gianluca Mauro
- How to craft and validate optimal prompts for consistent, high-quality outputs.
- Strategies for using ChatGPT to write long-form documents like essays and business plans.
- How to build and manage a custom prompt library tailored to your specific needs.
- Techniques for integrating ChatGPT into existing business workflows to enhance productivity and innovation.