FreeCourse Logo
FreeCourse.io
Verified CouponsFree CoursesJobsBlog
Categories
Home/Courses/Agentic AI for Absolute Beginners — A 52 Week Course
Agentic AI for Absolute Beginners — A 52 Week Course
Development100% OFF

Agentic AI for Absolute Beginners — A 52 Week Course

Udemy Instructor
1(606 students)
Self-paced
All Levels

About this course

This course contains the use of artificial intelligence. Agentic AI for Absolute Beginners — A 52-Week Course is a complete, beginner-friendly learning journey designed to help you understand, design, test, and demonstrate practical AI agents. No previous programming, automation, machine learning, or artificial intelligence experience is required.

You will begin by learning what agentic AI is and how agents differ from chatbots and traditional workflows. You will explore goals, tasks, actions, decisions, observations, feedback loops, planning, iteration, and human oversight. These concepts will help you understand how agents move beyond answering questions and begin completing structured tasks.

The course introduces prompt engineering for AI agents, including clear instructions, context, constraints, examples, output formatting, tables, checklists, and JSON. You will learn how to break complex goals into manageable steps and create reliable workflows that are easier to test and improve. You will then explore AI tool use, including web search, calculators, APIs, files, and external actions.

You will learn how agents gather information, verify sources, call tools, inspect results, and decide what to do next. Memory, context management, planning, reflection, correction, and retry logic are explained using approachable examples. A gradual introduction to Python for AI agents covers variables, data types, functions, loops, conditionals, lists, dictionaries, scripts, APIs, requests, responses, and model integration.

You will use these foundations to understand how simple assistants and agent workflows are created. Practical modules introduce research helpers, writing assistants, data helpers, support agents, email assistants, scheduling assistants, meeting assistants, and internal knowledge assistants. You will also compare AI agents vs automation workflows so you can select the right design for each problem.

The course covers retrieval-augmented generation, document grounding, chunking, contextual prompts, citations, and hallucination reduction. You will learn how agents can work with files and trusted knowledge rather than relying only on a model’s existing knowledge. Reliability and safety are central throughout the program.

You will study agent evaluation, debugging, guardrails, privacy, restricted actions, human approvals, responsible AI, logging, tracing, observability, cost management, deployment, and maintenance. You will also explore introductory multi-agent systems, including planner, researcher, writer, reviewer, executor, and coordinator roles. You will learn when specialized agents add value and when a simpler workflow is more reliable.

During the final eight weeks, you will complete mini-projects and build a portfolio-ready capstone. You will define the problem, choose tools, design the workflow, add guardrails, test reliability, improve the user experience, document the system, and present a final demonstration. By the end of this 52-week agentic AI course, you will have a practical foundation in AI agents, prompting, tools, memory, workflows, Python, APIs, RAG, automation, evaluation, safety, and deployment.

Skills you'll gain

Data ScienceEnglish

Available Coupons

Loading...

Course Information

Level: All Levels

Suitable for learners at this level

Duration: Self-paced

Total course content

Instructor: Udemy Instructor

Expert course creator

This course includes:

  • 📹Video lectures
  • 📄Downloadable resources
  • 📱Mobile & desktop access
  • 🎓Certificate of completion
  • ♾️Lifetime access
$0$93.99

Save $93.99 today!

Enroll Now - Free

Redirects to Udemy • Limited free enrollments

Share this course

https://freecourse.io/courses/agentic-ai-for-absolute-beginners-a-52-week-course

You May Also Like

Explore more courses similar to this one

Machine Learning & Predictive Modeling: Practice Exams
Development
0% OFF

Machine Learning & Predictive Modeling: Practice Exams

Udemy Instructor

Having a massive dataset is useless if you cannot extract predictive value from it. Welcome to the Machine Learning & Predictive Modeling practice assessments! In the modern business analytics ecosystem, companies do not just want to know what happened in the past; they want algorithms that predict what will happen next. This comprehensive practice test course provides you with 200 expertly crafted, highly unique practice questions designed to simulate the rigorous technical assessments given during data science engineering interviews.Across these four rigorous practice exams, you will be thrown into high-stakes algorithmic scenarios. You will test your ability to train house price prediction regression models using Kaggle datasets, build deep learning customer churn models using TensorFlow and Keras, and develop complex energy efficiency regression models. The questions push you to evaluate deep mathematical trade-offs: When should you prioritize Recall over Precision? Why does a Random Forest handle non-linear data better than a standard Logistic Regression? How does Dropout regularization prevent a neural network from overfitting?Every single question in this course is unique and includes a detailed explanation of the "why" behind the correct algorithmic approach. By reviewing these explanations, you will learn industry-standard methodologies for Hyperparameter Tuning (GridSearchCV) and preventing catastrophic data leakage. If you are preparing for a career as a Data Scientist, refining your predictive models, or aiming to dominate Kaggle competitions, this is your ultimate testing ground. Enroll today and train your model!Course locale: English (US) Course instructional level: Intermediate Level Course category: Development Course subcategory: Data Science

0.0•629•Self-paced
FREE$98.99
Enroll
AI in Healthcare: A-Z Guide on Tech, Applications & Ethics
Development
0% OFF

AI in Healthcare: A-Z Guide on Tech, Applications & Ethics

Udemy Instructor

Are you ready to be part of the biggest transformation in the history of medicine?Artificial Intelligence is no longer a futuristic concept—it is reshaping healthcare right now. From diagnosing cancer earlier than humanly possible to discovering life-saving drugs in record time, AI is the new nervous system of modern medicine.Welcome to AI in Healthcare: A-Z Guide on Tech, Applications & Ethics, the most comprehensive, practical, and accessible guide.Whether you are a clinician, a healthcare administrator, a medical student, a Pharmacist, a Nurse, or a technologist, this course will strip away the hype and give you a deep, actionable understanding of how AI works, where it is applied, and the ethical challenges we must navigate.We focus on "Augmented Intelligence"—the vision where AI does not replace healthcare professionals, but elevates them, automating burnout-inducing tasks and providing superpowers in diagnostics and decision-making.What You Will Learn:Master the AI Toolkit: Understand the core technologies driving the revolution, including Machine Learning (ML), Deep Learning, Natural Language Processing (NLP), Computer Vision, and Medical Robotics.Revolutionize Diagnostics: Discover how Convolutional Neural Networks (CNNs) are acting as a radiologist’s co-pilot to detect cancer, diabetic retinopathy, and neurological disorders like Alzheimer's.Reinvent Drug Discovery: Learn how AI is solving the pharma R&D crisis by accelerating target identification, virtual screening, and clinical trials (featuring case studies like BenevolentAI).Personalize Medicine: Explore the "N-of-1" revolution, from AI-driven oncology treatment plans to precision robotic surgery with the da Vinci 5 system.Optimize Hospital Operations: See how Predictive Analytics and Ambient AI Scribes are tackling clinician burnout, managing patient flow, and automating clinical documentation.Navigate the "Implementation Hurdles": Understand the critical hurdles of HIPAA & Data Privacy, Algorithmic Bias, FDA Regulation, and EHR Interoperability.Master AI Ethics: Tackle the tough questions regarding the "Black Box" problem, Explainable AI (XAI), patient accountability, and informed consent.Future-Proof Your Career: Get a look at the 5-10 year horizon, including Generative AI, Synthetic Data, Federated Learning, and the rise of the Augmented Clinician.Course Curriculum Breakdown:Module 1: The Revolution Begins We define AI in a clinical context and explore the "Perfect Storm" driving this shift: the Data Deluge (Genomics, EHRs), Exponential Computing Power (GPUs), and the economic necessity of modern healthcare.Module 2: The Core Technologies No coding required! We break down complex tech into simple terms. You will understand Supervised vs. Unsupervised Learning, how Neural Networks mimic the brain, and how NLP unlocks the 80% of medical data trapped in doctors' notes.Module 3: AI in Diagnostics Dive into Radiology and Digital Pathology. We analyze how AI detects lung and breast cancer in CTs/MRIs, screens for blindness, and assists pathologists with tissue sample analysis. Spotlight: GE Healthcare, Aidoc, Paige AI.Module 4: Pharma & Drug Discovery See how AI cuts drug development timelines from years to months. We cover high-speed virtual screening, predicting drug toxicity, and optimizing clinical trials.Module 5: Personalized Medicine & Surgery Move beyond "one-size-fits-all." Learn how AI tailors oncology treatments based on your genome (Tempus case study) and provides "force feedback" and integrated intelligence in robotic surgery (Intuitive Surgical & Medtronic).Module 6: Hospital Operations Tackle the crisis of burnout. Learn how AI automates medical coding, creates optimized schedules, and uses predictive analytics to manage hospital bed capacity and patient flow.Module 7: Patient Engagement Shift from reactive to proactive care. Explore the "Digital Front Door," Remote Patient Monitoring (RPM) for chronic conditions (Diabetes, CVD), and 24/7 AI Chatbots for triage and mental health support.Module 8: The Implementation Gauntlet We take an honest look at the barriers: The risk of re-identification in data, the dangers of Algorithmic Bias in health equity, navigating FDA approval pathways (510(k) vs. De Novo), and the cost of integration.Module 9: The Moral Compass (Ethics) We tackle the "Black Box" problem—how can we trust an AI if we don't know how it thinks? We discuss the rise of Explainable AI (XAI), liability when AI makes a mistake, and the evolution of informed consent.Module 10: The Future Horizon (5-10 Years) Prepare for what’s next. We cover Generative AI for synthetic data creation, Federated Learning for privacy-preserving collaboration, and the essential need for "Algorithmic Literacy" in medical education.Join us today to bridge the gap between medicine and technology. Enroll now to become a leader in the era of Augmented Intelligence!

0.0•2.0K•Self-paced
FREE$96.99
Enroll
Machine Learning & AI Fundamentals: Practice Exams
Development
0% OFF

Machine Learning & AI Fundamentals: Practice Exams

Udemy Instructor

We are living in the golden age of Artificial Intelligence. However, simply knowing how to import a library and call .fit() and .predict() is no longer enough to secure a high-paying job in data science. Companies are looking for engineers who understand the underlying mathematics of their models. They need professionals who know exactly why a neural network is overfitting, how to optimize a learning rate during gradient descent, and when to prioritize Recall over Precision in life-or-death classification models. Welcome to the Machine Learning & AI Fundamentals practice assessments!This comprehensive practice test course provides you with 200 realistic, highly technical questions modeled directly after the grueling data science interviews conducted by FAANG companies and top-tier research institutions. Across these four rigorous practice exams, you will face direct, scenario-based challenges spanning a massive array of industries. You will be tested on your ability to deploy Keras-based house price regression models, build fraud detection pipelines for major banking clients, and architect transformer models for real-time social media sentiment analysis.The questions in this course cut through the theoretical fluff and dive straight into practical application. You will be challenged on the nuances of categorical cross-entropy, the mathematical logic behind Gini Impurity in Decision Trees, and the architectural differences between CNNs and RNNs. If you are preparing to defend an academic submission, pivot your career into machine learning engineering, or prove that you can build models that actually scale in production environments, this is your ultimate testing ground. Enroll today and start optimizing your algorithms!Course locale: English (US) Course instructional level: Advanced Level Course category: Development Course subcategory: Data Science

0.0•616•Self-paced
FREE$98.99
Enroll
FreeCourse LogoFreeCourse

Freecourse.io brings you high-quality online courses with free certificates to help you upskill, boost your career, and achieve your goals anytime, anywhere.

Resources

  • Courses
  • Jobs
  • Categories
  • Features

Company

  • About
  • Blog
  • Contact

Legal

  • Privacy
  • Terms
  • Cookies
  • Licenses

© 2026 FreeCourse. All rights reserved.