Báo giá khóa đào tạo Chương trình đào tạo Computer Science dành cho Du học sinh

Giới thiệu khóa đào tạo

The International Computer Science Accelerator Program is a 10-month intensive training pathway designed for students preparing to study abroad in Computer Science, Software Engineering, or Data & AI–related majors. The program focuses entirely on core IT competencies, providing a strong foundation and practical skills through hands-on learning and real-world projects.

Across four structured semesters, learners build comprehensive capabilities in:
•   Full-Stack Web Development (HTML, CSS, JavaScript, Node.js, React.js)
•   Python Web Development (Django / Flask)
•   Mobile Application Development (Flutter)
•   Data Science & AI (Python, R, Machine Learning, Deep Learning)
•   AI for Automation (AI Agent N8N, Microsoft Power Automate)

Each semester is divided into specialized modules, featuring:
•   Real case studies from enterprises
•   Weekly practical exercises
•   Mini-Projects at the end of every semester
•   An applied learning model aligned with the expectations of international colleges and universities

The program is optimized for students aiming to:
•   Build a strong academic foundation before entering international CS programs
•   Develop a competitive portfolio for university applications
•   Gain practical IT experience comparable to first-year CS students abroad
•   Explore multiple fields in tech to shape their future academic major

With a balance of theory, hands-on practice, and project-based learning, the program equips learners with essential skills, technical confidence, and a global mindset—ensuring they are fully prepared for international academic environments and future tech careers.

Bảng báo giá & ưu đãi

Tên khóa học	Hình thức	Học phí gốc	Học phí ưu đãi	Ưu đãi nhóm
Chương trình đào tạo Computer Science dành cho Du học sinh	Trực tiếp	260,000,000	260,000,000	260,000,000
	Trực tuyến	260,000,000	260,000,000	260,000,000

Mục tiêu khóa học

Upon completing the International Computer Science Accelerator Program, learners will be able to:

1. Demonstrate Strong Foundations in Computer Science

-   Understand core CS concepts including data structures, algorithms, networking, and software architecture.
-   Apply computational thinking to analyze and solve technical problems effectively.
-   Use industry-standard tools such as Git, GitHub, IDEs, and project management workflows.

2. Build Full-Stack Web Applications

-   Develop responsive and interactive web interfaces using HTML, CSS, JavaScript, and React.js.
-   Design and implement backend systems using Node.js, Express, and database technologies.
-   Integrate frontend and backend components to build complete full-stack applications.
-   Deploy web applications to cloud platforms.

3. Develop Modern Web Applications with Python Frameworks

-   Build dynamic web systems using Django or Flask.
-   Work with ORM, API development, authentication, and middleware.
-   Design scalable web architectures following international best practices.

4. Create Cross-Platform Mobile Applications

- Use Flutter & Dart to develop mobile applications for iOS and Android.
- Build UI/UX flows, integrate APIs, manage states, and deploy apps.

5. Perform Data Analysis and Build AI Models

-   Use Python & R for data exploration, data cleaning, visualization, and statistical analysis.
-   Build, train, and evaluate Machine Learning and Deep Learning models.
-   Apply AI techniques in classification, regression, clustering, NLP, and Computer Vision.
-   Interpret and present insights through dashboards, reports, and visualizations.

6. Automate Workflows with Modern AI Tools

-   Build automation workflows using AI Agent N8N and Microsoft Power Automate.
-   Integrate APIs, webhooks, and AI models into automated business processes.
-   Design real-world automation systems aligned with enterprise needs.

7. Work Professionally in Tech Projects

-   Apply Agile/Scrum methodologies in team-based development.
-   Use version control, coding standards, and collaborative workflows.
-   Build Mini-Projects every semester and complete a capstone portfolio-ready project.
-   Demonstrate problem-solving, communication, documentation, and presentation skills.

8. Develop a Strong International Portfolio

-   Build a portfolio of web, mobile, data science, and AI projects aligned with global education standards.
-   Prepare fully for university applications: personal statements, project showcase, GitHub profile, and technical interviews.
-   Gain confidence to join Computer Science programs abroad at an advanced level.

Nội dung khóa học

Tên bài học	Nội dung	Thời lượng
SEMESTER 1 — WEB DEVELOPMENT FOUNDATION	SEMESTER 1 — WEB DEVELOPMENT FOUNDATION	120 HOURS
Module 1: CS Foundations & Git/GitHub	Detailed Content • Computer Systems, OS, CPU, Memory, I/O • Basic Networking: IP, Domain, DNS, HTTP/HTTPS • Software Development Process: Agile, Scrum • Basic Git: init, clone, commit, push • Advanced Git: branch, merge, pull request Case Study • Team collaboration using one shared GitHub repository. Learning Outcome • Ability to work with Git/GitHub like an international developer.	12 hours
Module 2: HTML & CSS	Detailed Content • HTML page structure • Semantic HTML5 • CSS basics: selectors, box model • Advanced CSS: Flexbox, Grid • Responsive Web Design • Basic UI/UX fundamentals • Converting Figma designs into HTML/CSS Case Study • Clone UI layouts: Shopee / Starbucks / Tiki. Learning Outcome • A fully responsive landing page.	24 hours
Module 3: JavaScript ES6+	Detailed Content • ES6 features: let/const, arrow functions, spread, destructuring • DOM manipulation • Event handling • AJAX & Fetch API • JSON • LocalStorage Case Study • To-Do List / Notes App / Shopping Cart Web App. Learning Outcome • Frontend web application with full CRUD functionality.	24 hours
Module 4: ReactJS	Detailed Content • SPA concepts • Component lifecycle • Props & State • Hooks (useState, useEffect, useContext) • Routing with React Router • State management: Context API / Redux • API Integration • UI Libraries: Material UI, Ant Design Case Study • Product Management Dashboard (CRUD + Filter + Search). Learning Outcome • A complete React application connected to a real API.	36 hours
Module 5: NodeJS & Express (12 hours)	Detailed Content • NodeJS runtime environment • Express routing • REST API development • Database connection (MongoDB/MySQL) • JWT Authentication • Error handling & middleware Case Study • Authentication API (Sign up / Login) + Product CRUD. Learning Outcome • Backend API ready for frontend consumption.	12 hours
⭐ Mini Project (Full-Stack)	• Students build one complete system: • E-commerce Mini App • Booking System • Social Network Mini App	12 hours
SEMESTER 2 — PYTHON WEB DEVELOPMENT	SEMESTER 2 — PYTHON WEB DEVELOPMENT	120 HOURS
Module 1: Python Foundations	Detailed Content • Variables, functions, loops, conditionals • OOP: class, object, inheritance, polymorphism • Exception handling • File I/O • Data structures: List, Dict, Tuple, Set • Virtual environments Case Study • HR Management System using Python OOP. Learning Outcome • Ability to use Python to solve real-world business logic.	18 hours
Module 2: Django	Detailed Content • Django project structure • MVT architecture • Models & ORM • Templates & Forms • Authentication & Authorization • Django Admin customization • Django REST Framework (API) • File upload, pagination, filtering • Email + background tasks Case Study • Blog Management System • Appointment Booking System Learning Outcome • Web application from zero to production-ready.	36 hours
Module 3: Flask	Detailed Content • Flask routing • Jinja2 templates • Blueprint structure • REST API • JWT authentication • Database integration (SQLite/PostgreSQL) Case Study • Booking or Healthcare API system. Learning Outcome • Ability to build lightweight and high-performance APIs.	24 hours
Module 4: Database & Cloud Deployment	Detailed Content • PostgreSQL / MySQL fundamentals • SQL queries (Join, Index, Aggregation) • Docker basics • Deploy Django/Flask to AWS / Render / Railway • Environment variables, DNS, HTTPS/SSL Case Study • Deploy a Python web app to a real cloud service. Learning Outcome • Practical deployment skills for modern applications.	18 hours
⭐ Mini Project	• Social Network API • E-commerce Backend • Online Learning Management System API	24 hours
SEMESTER 3 — MOBILE DEVELOPMENT & DATA ANALYTICS	SEMESTER 3 — MOBILE DEVELOPMENT & DATA ANALYTICS	120 HOURS
Module 1: Flutter	Detailed Content • Dart fundamentals • Widget tree & layouts • Navigation • State management: Provider / Bloc • API Integration • Local data storage • Responsive UI Case Study • Notes app / Task manager / Ride-booking mini app. Learning Outcome • Cross-platform mobile app for Android & iOS.	36 hours
Module 2: Python for Data Analysis	Detailed Content • Numpy & Pandas • Data cleaning • Data transformation • Data visualization (Matplotlib, Seaborn) Case Study • Sales performance analysis across 12 months. Learning Outcome • Complete data analysis report.	24 hours
Module 3: R for Analytics	Detailed Content • R language basics • dplyr, tidyr • ggplot2 visualization • Statistical testing • Regression modeling Case Study • House price prediction using regression models. Learning Outcome • Professional-level data analytics report.	24 hours
Module 4: Machine Learning	Detailed Content • ML workflow • Train/Test split • Classification (KNN, SVM, Decision Tree) • Regression (Linear, Polynomial) • Clustering (K-Means) • Model evaluation techniques Case Study • Customer segmentation • Churn prediction Learning Outcome • Build, evaluate and present ML models.	24 hours
⭐ Mini Project	• Recommendation System • Forecasting Model • Classification Model	12 hours
SEMESTER 4 — AI, AUTOMATION & CAPSTONE	SEMESTER 4 — AI, AUTOMATION & CAPSTONE	120 HOURS
Module 1: AI for Automation (N8N, Power Automate)	Detailed Content • Workflow Automation concepts • Triggers & Actions • API Integration • Build custom AI Agents • Power Automate Cloud • PowerApps Forms • Automating email, approvals, and reporting Case Study • Automated approval workflow • Daily automated reporting system	30 hours
Module 2: Applied AI	Detailed Content • NLP fundamentals • Text classification • Sentiment analysis • Computer Vision basics • OCR pipeline • Generative AI: LLMs, Embeddings, RAG • Vector databases (Chroma/FAISS) Case Study • AI Chatbot • Invoice OCR + data extraction	30 hours
Module 3: System Design	Detailed Content • Scalability • API Gateway design • Caching layers • Load balancing • Microservices • Database sharding • High availability architecture Case Study • Design a system similar to Grab/Uber/Amazon	24 hours
Module 4: Portfolio & Interview Preparation	Detailed Content • Building a professional portfolio website • Optimizing GitHub profile • International-standard resume (US/UK/CA/AUS) • Technical interview preparation • Mock interview sessions	12 hours
⭐ Capstone Project	Students select one track: • Option 1: AI Automation Platform Web App + Database + N8N + AI Agent • Option 2: AI-powered Mobile App Flutter App + ML Model • Option 3: Data Analytics Platform Dashboard + Forecasting + Automation Final presentation to an evaluation panel.	24 hours

Điều kiện Cần & Đủ

✔ Prerequisites

To ensure students can follow the program effectively, learners should meet the following prerequisites:

1. Academic Background

- Completed grade 9 or higher (for high-school students), or
- Currently studying in high school/college interested in Computer Science.

2. Basic Computer Literacy

-   Ability to use a computer confidently (Windows or macOS).
-   Familiarity with basic software: web browser, file management, typing skills.
-   Ability to install software following instructions.

3. English Proficiency

-   Basic English reading comprehension (A2 → B1 level).
-   Ability to understand simple technical instructions in English.
-   Note: No advanced English is required; technical English will be improved throughout the program.

4. Mindset & Learning Attitude

-   Curiosity and passion for technology, programming, and digital tools.
-   Willingness to learn by doing through projects and case studies.
-   Commitment to follow at least 10 months of intensive learning.

5. Personal Laptop Requirements

-   CPU: Intel i5 / Ryzen 5 or higher
-   RAM: Minimum 8GB (recommended 16GB for Data Science & AI)
-   Storage: 256GB SSD or higher
-   Stable internet connection

6. No Prior Programming Experience Required

- Students do not need to know coding beforehand.
- The program starts from fundamentals and progresses to advanced topics.

✔ Requirements

To successfully complete the program and apply the acquired knowledge in real-world projects, students are expected to meet the following requirements:

1) Attendance & Learning Commitment

-   Attend at least 80% of classes in each module.
-   Actively participate in exercises, group work, and in-class coding sessions.
-   Maintain consistent study habits for a minimum of 6–8 hours of self-study per week.

2) Completion of All Assignments

-   Finish weekly coding tasks and quizzes.
-   Complete all case studies, lab exercises, and mini-projects at the end of each semester.
-   Submit assignments on time via LMS/GitHub.

3) Build and Maintain a Personal GitHub Portfolio

-   Push code regularly to GitHub.
-   Maintain clean, readable, well-documented code.
-   Organize projects clearly to serve as part of a university application portfolio.

4) Technical Proficiency Development

-   By the end of the program, learners are expected to:
-   Understand fundamental programming concepts and be able to write functional programs independently.
-   Build at least 1–2 working applications per semester (web, mobile, Data/AI).
-   Apply learned tools (Python, React, Flutter, Django, Data Science, Automation AI) in real mini-projects.

5) Soft Skills & Professional Skills

-   Communicate effectively in English during presentations and discussions.
-   Collaborate in group projects using Agile/Scrum or similar teamwork methodologies.
-   Practice problem-solving and debugging independently.

6) Final Project Completion

-   Successfully complete a capstone project that demonstrates mastery in at least one focus area:
•   Web Development
•   Mobile Development
•   Data Science & AI
•   AI Automation
-   Present the final project professionally (slides, demo, documentation).

7) Tools & Technical Requirements

- Laptop is maintained in good condition and software required for modules is installed properly.
- Ability to perform troubleshooting with support from instructors when needed.

Thông tin Giảng viên

Henry Nguyễn

🔹15+ năm kinh nghiệm
🔹Technical Consultant tại IMIC
🔹Chuyên môn: Lập trình Web Full-stack Data Engineer & AI

Toàn Trần

🔹10+ năm kinh nghiệm
🔹Project Manager tại Cyberlogitec
🔹Chuyên môn: Lập trình Web Full-stack & Mobile apps, Data Engineer & AI

Tại sao học viên lại chọn IMIC?

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Giờ làm việc

Thứ 2 – Thứ 6: 08:30 – 21:30
Thứ 7 – Thứ 7: 08:30 – 12:00

Phòng tuyển sinh

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Phòng tuyển sinh

Ms Trân – Admissions Team

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