Free Course
Complete Beginner
Sinhala + English Terms
Ai Zero to Hero in 7 Days
From Complete Beginner to Your First Practical Ai Solution
Understand the complete world of artificial intelligence, experience its major methods and design your first practical Ai solution through structured Sinhala explanations, English technical terminology, activities, quizzes and visual demonstrations.
The YouTube link is temporary and will be replaced when the course introduction video is published.
Honest course promise
Build a correct Ai foundation—not false overnight mastery
This course does not claim to make you an Ai engineer in seven hours. It gives you the mental map, terminology, practical exposure and direction required to continue into deeper Ai Panthiya learning paths.
What the course will help you do
- Understand the complete Ai landscape.
- Build a strong beginner foundation.
- Experience major concepts and workflows.
- Identify the deeper path that suits you.
- Design your first practical Ai solution.
What the course does not promise
- Instant professional expertise.
- Job readiness after seven hours.
- Mastery of every Ai algorithm.
- Complete advanced mathematical knowledge.
- No need for further study.
Who should begin here?
Designed for learners who need a clear starting point
The course is suitable for complete beginners and partially experienced learners who want a connected view of Ai before choosing a deeper technical or professional pathway.
Complete Beginners
Start without programming or advanced mathematical knowledge.
Students
Understand the major fields, terminology and possible career directions.
Working Professionals
Learn how Ai connects to business, productivity and practical problem-solving.
Developers
See how models, APIs, databases, RAG, agents and deployment connect.
Data Learners
Connect data, statistics, machine learning and forecasting into one system.
Future Ai Researchers
Build the orientation needed before entering deeper theory and experiments.
Course outcomes
What you will understand by the end
You will leave with a complete beginner map of Ai and a clear next learning direction.
Begin the CourseExplain Ai, machine learning, deep learning and generative Ai correctly.
Understand data, features, labels, models, training, testing and inference.
Recognize classification, regression, clustering, anomaly detection, recommendation and forecasting problems.
Understand the role of programming, mathematics, statistics, databases, cloud and hardware.
Use generative Ai through structured prompting and verification.
Run or observe a complete machine-learning workflow.
Understand neural networks, transformers, embeddings, RAG and Ai agents.
Recognize production, security, privacy, fairness and responsible-Ai requirements.
Design a one-page Ai solution for a real-world problem.
Seven-day curriculum
One connected journey through the complete Ai landscape
Each day contains six connected lessons, one practical activity and a daily knowledge check.
Day 1
Available
The Complete Map of Artificial Intelligence
Understand the complete Ai landscape and choose a personal learning pathway.
- What artificial intelligence really means
- Ai, machine learning, deep learning and generative Ai
- The five main ways Ai solves problems
- Ai software and hardware ecosystems
- Ai careers and learning pathways
Day 2
Coming Soon
Data, Mathematics and Statistics Behind Ai
Inspect a dataset and understand how quantitative reasoning supports Ai.
- Data types, features and labels
- How computers represent the world
- Mathematics for Ai
- Statistics and probability
- Data cleaning, bias and leakage
Day 3
Coming Soon
How Machine Learning Actually Works
Understand and experience the complete machine-learning workflow.
- Models, algorithms and predictions
- Training, validation, testing and inference
- Regression and classification
- Major supervised algorithms
- Overfitting and generalization
Day 4
Coming Soon
Pattern Discovery, Forecasting and Evaluation
Recognize the major Ai task families and evaluate model results.
- Unsupervised learning
- Clustering
- Dimensionality reduction
- Recommendation and association rules
- Forecasting and evaluation metrics
Day 5
Coming Soon
Deep Learning and Generative Ai
Understand modern neural and generative systems without hype.
- Neural networks and representation learning
- Backpropagation and gradient descent
- Vision, language and speech
- Transformers and large language models
- Prompting, hallucination and verification
Day 6
Coming Soon
Building Ai Applications
Understand how Ai models become useful software products.
- Models versus complete applications
- APIs and model access
- Embeddings and vector databases
- Retrieval-Augmented Generation
- Ai agents, tools and workflows
Day 7
Coming Soon
Production, Hardware, Responsibility and Final Project
Connect the complete Ai system and design a practical final solution.
- From notebook to production
- Cloud, MLOps and LLMOps
- Ai hardware and edge Ai
- Security, privacy and responsible Ai
- Final Ai Solution Canvas
Daily learning format
Six connected lessons every day
Each day follows the same learning rhythm so that you understand, practise and connect the topic rather than simply watching unrelated videos.
Orient
Understand the day’s topic, purpose and position in the Ai map.
Understand
Learn the foundational theory through visual intuition.
Mechanism
See how the concept operates technically.
Demonstrate
Observe the concept in a real tool, model, dataset or workflow.
Practise
Complete a guided worksheet, notebook or practical task.
Integrate
Correct misconceptions, complete the quiz and connect the day.
Learning evidence
Show what you understand through practical outputs
Completion is based on active participation, not only video watching.
Daily Retrieval Quizzes
Complete short quizzes that test understanding and correct common misconceptions.
Suggested target: 70% overallDaily Practical Activities
Complete pathway maps, data tasks, model activities, workflow designs and prompt exercises.
Complete at least 5 of 7Final Ai Solution Canvas
Design one complete Ai solution including users, data, workflow, evaluation, risks and human oversight.
Complete all 10 sections
Final project
Design your first complete Ai solution
On Day 7, you will combine the entire course into a one-page practical solution design.
View Course ResourcesProblem
Users
Data
Ai Task
Model or Tool
Workflow
Evaluation
Risks
Human Oversight
Value
Free course resources
Use the course materials alongside every lesson
Downloadable resources will be connected as production is completed.
Complete Ai Map
A visual overview of Ai fields, foundations, software, hardware and specialist pathways.
View resourcePersonal Ai Pathway Map
Identify your current position, target role and next three learning stages.
View resourceDaily Master Quiz Pack
Review the main ideas and identify misunderstandings after each day.
View resourceFirst Machine-Learning Workflow
Run a simple model, change one setting and compare the result.
View resourceStructured Prompt Template
Improve weak prompts through role, task, context, constraints and output format.
View resourceAi Solution Canvas
Design a responsible, useful and measurable Ai solution.
View resource
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Important course boundary
Completion is a foundation—not a professional qualification
This rapid course provides orientation, terminology, practical exposure and direction. Professional capability requires deeper study, projects, evaluation, deployment experience and responsible practice.
Your journey starts here
Begin Day 1 and understand the complete Ai map
Start with the correct foundation, identify your preferred learning path and prepare for the remaining six days.