Three Courses, One Progression
Each course is complete in itself and useful on its own terms. Together they take you from first Python script to deployed AI application.
Back to HomeHow the Courses Are Structured
Every course at Minda Cerdas follows the same underlying rhythm regardless of the topic. This consistency makes it easier to settle into each new intake.
Short Concept Videos
Recorded sessions introduce a small number of ideas clearly and concisely. You can rewatch at any time.
Guided Exercises
Apply what you just saw in a structured exercise that is part of the lesson, not an afterthought.
Weekly Assignment
A slightly larger task that requires combining concepts from the week. Reviewed by an instructor with written feedback.
Live Session
A weekly evening session to ask questions, see live demonstrations, and hear how other learners are working through the same material.
AI & Python Foundations
A gentle starting point for those new to building with AI. Covers core Python and the ideas behind machine learning at a pace suited to curious beginners and career-changers. Designed to fit around other commitments, with recorded lessons, weekly live sessions, and a friendly community space.
What You Will Cover
- Python syntax, data types, and control flow
- Working with lists, dictionaries, and functions
- Introduction to NumPy and Pandas for data handling
- Core machine learning concepts and terminology
- A guided end-of-course practice project
Week by Week
RM 238
Applied Machine Learning
For learners with some Python experience who want to build and train their own models. Covers data preparation, common algorithms, and how to evaluate results carefully. Includes hands-on assignments with mentor feedback and a portfolio piece developed over the final weeks.
What You Will Cover
- Exploratory data analysis and feature engineering
- Supervised learning — regression, classification, trees
- Model evaluation — metrics, cross-validation, overfitting
- Introduction to neural networks with PyTorch
- Portfolio project with code review and written feedback
Week by Week
RM 285
Building & Deploying AI Apps
For learners comfortable with machine learning who want to develop and ship complete AI-driven applications. Covers working with modern models, integrating them into real software, and deploying thoughtfully. The course ends with a capstone application reviewed by a mentor.
What You Will Cover
- Working with large language models and modern AI APIs
- Backend integration and API design for AI services
- Deployment to cloud platforms — containerisation and hosting
- Monitoring, logging, and maintaining a deployed AI system
- Capstone project — end-to-end AI application with mentor review
Key Milestones
RM 327
Course Comparison
Use this table to find your starting point. If you are unsure, contact us and we will help you decide.
| Feature / Who It Suits | AI & Python Foundations | Applied ML | Deploying AI Apps |
|---|---|---|---|
| Prior Python experience needed | None | Basic | Comfortable |
| Duration | 8 weeks | 10 weeks | 12 weeks |
| Portfolio output | |||
| Mentor feedback on assignments | |||
| Capstone review session | |||
| Deployment and cloud topics | |||
| Fee (RM) | 238 | 285 | 327 |
Technical Standards
These practices apply to every course, regardless of level.
Version Control from Day One
All course exercises use Git. This is not a separate topic — it is part of how you submit work from the first week.
Privacy and Data Ethics
Each course addresses data responsibility — what you can and cannot do with data, and why these questions matter in practice.
Code Readability Standards
Feedback on assignments includes comments on code clarity and structure. Writing readable code is treated as a skill worth developing.
Updated Before Each Intake
Tooling changes in AI. Course materials are reviewed and revised between cohorts — not left static while the field moves on.
Learner Data Handled Carefully
Work submitted for feedback is stored securely and not shared with third parties. Enrolment data follows Malaysia's PDPA requirements.
Feedback Within Three Days
Assignment submissions receive written feedback from an instructor within three business days of the submission deadline.
Transparent Fees
All prices are in Malaysian Ringgit. One payment per course — no subscriptions, no extras.
AI & Python Foundations
8 weeks · Beginner
RM 238
per course enrolment
- All recorded lessons
- Weekly live sessions
- Assignment feedback
- Community access
- Completion certificate
Applied Machine Learning
10 weeks · Intermediate
RM 285
per course enrolment
- All recorded lessons
- Weekly live workshops
- Assignment + code review
- Portfolio project
- Completion certificate
Building & Deploying AI Apps
12 weeks · Advanced
RM 327
per course enrolment
- All recorded lessons
- Live sessions + 1-on-1 guidance
- Capstone project
- Mentor capstone review
- Completion certificate
Not Sure Where to Begin?
Send us a message with a brief note about your background and what you want to learn. We will suggest the right course for you without any pressure to decide immediately.
Ask Us a Question