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12-Week AI Certification Program
New
142 students
12-Week AI Certification Program
Master AI Foundations, Machine Learning, Deep Learning, LLMs, Agents, Deployment, and Responsible AI in 12 Weeks
Created bySchool of AI
Last updated 6/2026
English
What you'll learn
- Understand the core concepts of Artificial Intelligence, including how AI systems work, where they are used, and how they create real-world impact.
- Build practical AI projects using Python, NumPy, Pandas, and common data processing techniques.
- Clean, analyze, visualize, and prepare data for Machine Learning and AI applications.
- Train, evaluate, and improve Machine Learning models for regression, classification, clustering, and predictive tasks.
- Understand the fundamentals of Deep Learning, neural networks, activation functions, backpropagation, and model training.
- Build beginner-friendly applications in Natural Language Processing, Computer Vision, and Large Language Models.
- Apply Prompt Engineering techniques to create better outputs from LLMs and AI assistants.
- Design and build basic AI Agents using tools, memory, vector databases, and automation workflows.
- Deploy AI applications using modern production concepts such as APIs, FastAPI, monitoring, logging, and optimization.
- Understand key principles of Responsible AI, including ethics, bias, governance, privacy, security, and risk management.
- Complete hands-on labs and a final portfolio-ready capstone project that demonstrates practical AI skills.
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Course content
12 sections • 73 lectures • 23h 22m total length
Requirements
- No advanced AI or machine learning experience is required.
- Basic computer skills are helpful, such as installing software, using folders, and working with files.
- Basic programming knowledge is helpful, but the course starts with beginner-friendly Python concepts.
- A laptop or desktop computer is required to complete the hands-on labs and projects.
- Internet access is recommended for downloading tools, libraries, datasets, and course resources.
- Learners should be willing to practice coding, experiment with AI tools, and build projects step by step.
- Familiarity with basic math concepts such as averages, percentages, and simple graphs is helpful but not required.
- No prior experience with Machine Learning, Deep Learning, NLP, Computer Vision, LLMs, or AI Agents is required.
- The course is designed for beginners, professionals, students, developers, analysts, and anyone who wants to build practical AI skills.
- Most importantly, learners should come with curiosity, consistency, and a willingness to learn by building.
Description
This course contains the use of artificial intelligence.
12-Week AI Certification Program is a complete, hands-on learning journey designed to help you build practical skills across Artificial Intelligence, Python, Data Science, Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Large Language Models, AI Agents, Deployment, and Responsible AI.
This program starts with the foundations of AI and computing, helping you understand how intelligent systems work, how software has evolved from rule-based logic to learning-based systems, and how data, algorithms, and models power modern AI applications. You will set up your AI development environment and build your first intelligent system through a beginner-friendly rule-based AI lab.
As the course progresses, you will learn Python for AI development, including data structures, functions, modules, NumPy, and Pandas. These skills will prepare you to work confidently with real-world data. You will then explore data fundamentals, including data types, data sources, cleaning, preprocessing, exploratory data analysis, visualization, and pipeline development. Through hands-on labs, you will build practical data processing scripts and an end-to-end data pipeline.
The middle section of the program focuses on Machine Learning and Advanced Machine Learning. You will learn supervised learning, regression, classification, model evaluation, feature engineering, clustering, dimensionality reduction, hyperparameter tuning, and production-style ML workflows. These lessons will help you understand how to build, train, evaluate, and improve real ML models.
You will also explore Deep Learning, where you will learn neural networks, activation functions, backpropagation, model training, and framework-based development. From there, the course moves into Natural Language Processing, covering text processing, tokenization, embeddings, transformers, text classification, and chatbot-style applications. You will then study Computer Vision, including image processing, convolutional neural networks, object detection, transfer learning, and image classification apps.
In the advanced weeks, you will work with Large Language Models and Prompt Engineering, learning how to design effective prompts, use advanced prompting techniques, and build practical LLM applications. You will then move into AI Agents and Automation, where you will learn tool usage, function calling, memory systems, vector databases, multi-agent design, and autonomous workflows.
The final part of the program prepares you for real-world implementation through AI deployment, FastAPI, cloud deployment concepts, monitoring, logging, optimization, and production readiness. You will also learn AI governance, ethics, bias, security, privacy, and risk management, giving you the knowledge needed to build AI responsibly.
By the end of this 12-week AI certification, you will have completed 12 hands-on labs and a portfolio-ready capstone project. This course is ideal for beginners, professionals, developers, analysts, managers, and anyone who wants to gain practical, job-ready skills in Artificial Intelligence and build real AI systems from start to finish.
Who this course is for:
- Beginners who want a structured, step-by-step path into Artificial Intelligence without needing advanced technical experience.
- Professionals who want to understand how AI, Machine Learning, Deep Learning, LLMs, and AI Agents are used in real-world business and technology environments.
- Developers and aspiring developers who want to build practical AI projects using Python, data tools, ML models, APIs, and deployment workflows.
- Data analysts, business analysts, and tech professionals who want to expand their skills into Data Science, Machine Learning, and AI-powered applications.
- Students and career changers who want to build a strong foundation in AI and create portfolio-ready projects.
- Managers, product leaders, and business professionals who want to understand AI concepts, capabilities, risks, and practical use cases.
- Anyone interested in learning how to build AI systems from the ground up, including data pipelines, ML models, neural networks, NLP apps, computer vision apps, LLM assistants, and AI agents.
- Learners who want a hands-on certification-style program with weekly labs, real projects, and a final capstone project they can showcase.