Artificial Intelligence (HCCDA-AI) – Huawei Certified Cloud Developer Associate
- 12 Weeks
- On-campus
Course Overview
Huawei HCCDA-AI is a 3-month onsite professional training program designed to develop practical Artificial Intelligence and Machine Learning skills. The program prepares candidates for the Huawei Certified ICT Associate – Artificial Intelligence (HCCDA-AI) certification.
This industry-focused training covers AI fundamentals, Machine Learning concepts, Python programming, Huawei Cloud AI services, ModelArts, Deep Learning frameworks, Edge AI, AI application development, and real-world AI project implementation.
Students will gain hands-on experience developing AI solutions using Huawei Cloud AI technologies, including Huawei ModelArts, AI APIs, HiLens, Cloud AI integration, and MLOps workflows.
Training Details
Course Duration: 3 Months (12 Weeks)
Training Mode: Onsite Classroom + Practical Lab Training
Total Training Hours: 180 Hours
Theory: 74 Hours
Practical: 106 Hours
Weekly Hours: 15 Hours
Learning Environment: Classroom / Lab Based Training
Course Objectives
This program aims to:
- Build strong foundations in Artificial Intelligence and Machine Learning
- Understand AI development workflows
- Learn Huawei Cloud AI services and solutions
- Develop AI applications using Python
- Work with Huawei ModelArts for AI development and deployment
- Understand Deep Learning frameworks
- Build and test AI models
- Learn Edge AI development using Huawei HiLens
- Prepare learners for Huawei HCCDA-AI certification
What You Will Learn
1. Foundations of Artificial Intelligence & Machine Learning
Students will learn:
- Introduction to Artificial Intelligence
- History and evolution of AI
- Types and scope of AI
- Machine Learning fundamentals
- AI industry trends
- Generative AI and Edge AI concepts
- Huawei AI strategy and Cloud AI ecosystem
Practical Learning:
- Understanding AI use cases
- Exploring AI applications in different industries
- Preparing for Huawei AI certification pathway
2. Data Science Essentials for AI Development
Students will learn:
- Data preparation techniques
- Data handling and analysis
- Dataset management
- Data visualization concepts
- Machine Learning workflow
Practical Learning:
- Working with datasets
- Data cleaning and transformation
- Preparing data for AI models
3. Python Programming for AI & Cloud Developers
Students will learn:
- Python programming fundamentals
- Variables, functions, loops, and logic building
- NumPy for numerical computing
- Pandas for data manipulation
- Scikit-learn basics
- Python development environment for AI
Practical Learning:
- Writing Python programs
- Data analysis using Python
- Building basic Machine Learning models
4. Cloud Fundamentals for AI Applications
Students will learn:
- Cloud computing concepts
- AI and Cloud integration
- Huawei Cloud AI ecosystem
- Cloud-based AI application architecture
Practical Learning:
- Working with Huawei Cloud environment
- Understanding AI deployment workflows
5. AI Application Requirement Analysis & Design
Students will learn:
- AI project requirement analysis
- Functional and non-functional requirements
- AI solution planning
- Selecting suitable AI technologies
Practical Learning:
- Creating AI project requirement documents
- Designing AI solution architecture
- Mapping requirements with Huawei AI services
6. Huawei Cloud EI Services & AI APIs
Students will learn:
- Huawei Cloud EI platform
- AI service categories
- Vision AI services
- Natural Language Processing (NLP)
- Speech services
- OCR services
Practical Learning:
- Using Huawei AI APIs
- REST API integration
- Python SDK implementation
- Testing AI services
7. Hands-on AI APIs (OCR, NLP & Vision)
Students will learn:
- Optical Character Recognition (OCR)
- Image recognition
- Natural Language Processing applications
- AI API integration
Practical Learning:
- Using OCR APIs
- Extracting information from images
- Testing AI-powered applications
- Evaluating API performance
8. Huawei ModelArts & AutoML
Students will learn:
- Introduction to Huawei ModelArts
- AI development lifecycle
- Dataset management
- Model training
- Model evaluation
- AutoML concepts
- AI model deployment
Practical Learning:
- Creating AI projects in ModelArts
- Training AI models
- Using pre-trained AI models
- Fine-tuning models with custom datasets
9. Edge AI & Huawei HiLens
Students will learn:
- Edge AI concepts
- Huawei HiLens architecture
- AI deployment on edge devices
- Video analytics applications
Practical Learning:
- Deploying AI models on HiLens
- Creating event-based AI applications
- Testing real-time AI inference
10. Deep Learning Concepts & Frameworks
Students will learn:
- Neural networks fundamentals
- Deep Learning architecture
- CNN and RNN concepts
- TensorFlow and PyTorch frameworks
- Image classification models
Practical Learning:
- Building Deep Learning models
- Training image classification models
- Evaluating model performance
11. AI Model Testing, Evaluation & Optimization
Students will learn:
- AI testing methodologies
- Model performance evaluation
- Accuracy measurement
- Error analysis
- Model optimization techniques
Practical Learning:
- Testing AI applications
- Analyzing model results
- Improving AI model performance
12. MLOps & AI Deployment on Huawei Cloud
Students will learn:
- MLOps lifecycle
- AI workflow automation
- Model deployment pipelines
- Monitoring AI models
- Model drift detection
Practical Learning:
- Creating AI deployment workflows
- Using ModelArts with OBS and FunctionGraph
- Monitoring AI applications
13. Certification Preparation & Capstone Project
Students will complete:
- Huawei HCCDA-AI exam preparation
- Mock certification exams
- AI project development
- AI model deployment
- Final project presentation
Students will develop real-world AI solutions such as:
- Chatbots
- Smart retail solutions
- AI inspection systems
- Image recognition applications
Learning Outcomes
After completing Huawei HCCDA-AI training, students will be able to:
✅ Understand Artificial Intelligence and Machine Learning fundamentals
✅ Develop AI applications using Python
✅ Analyze and prepare datasets for AI projects
✅ Use Huawei Cloud AI services and APIs
✅ Build and deploy AI models using Huawei ModelArts
✅ Work with Deep Learning frameworks
✅ Develop Edge AI applications using Huawei HiLens
✅ Test and optimize AI solutions
✅ Understand MLOps and AI deployment workflows
✅ Prepare for Huawei HCCDA-AI certification
Who Should Enroll?
This course is suitable for:
Computer Science & IT Students
Students enrolled in:
- Computer Science
- Information Technology
- Software Engineering
- Artificial Intelligence
- Mechatronics
- Electrical/Electronics Engineering
- Computer Systems Engineering
Graduates & Postgraduates
Students looking to start careers in AI, Machine Learning, and Cloud AI.
IT Professionals
Professionals interested in upgrading their skills in:
- Artificial Intelligence
- Machine Learning
- Cloud Technologies
- Data Science
DIT Professionals
Candidates with Diploma in Information Technology and relevant IT experience can also apply.
Career Opportunities
After completing this training, learners can explore careers as:
- AI Engineer
- Machine Learning Engineer
- Data Science Associate
- Cloud AI Developer
- AI Application Developer
- Computer Vision Engineer
- NLP Developer
- MLOps Engineer
Relevant industries include:
- Technology Companies
- Telecommunication Industry
- Banking Sector
- Software Development Companies
- AI Solution Providers
The official curriculum lists career opportunities with organizations including Huawei, PTA, NADRA, SAP Pakistan, Accenture Pakistan, Devsinc, Fusemachines, Azure/AWS, Upwork, Fiverr, Toptal and other technology companies.
Why Choose ISDI Huawei Professional Training?
- 100% Free Huawei Professional Training
- Official Huawei Certification Preparation
- Onsite Practical Lab Training
- Industry-Relevant AI Curriculum
- Hands-on AI Projects
- Experienced Trainers
- Future-Ready Artificial Intelligence Skills
