Ai-powered App Development With Python & Tensorflow Training Course in Malta
Introduction
In the age of artificial intelligence, the ability to build intelligent applications is no longer optional—it's a critical skill. This AI-Powered App Development with Python & TensorFlow training course is designed to equip developers, data scientists, and digital innovators with the cutting-edge knowledge and tools to design, build, and deploy powerful AI-driven applications using Python and TensorFlow, two of the most widely used technologies in modern machine learning.
Participants will explore end-to-end AI development workflows—from data ingestion and preprocessing to neural network architecture design, training, evaluation, and real-time deployment. With real-world case studies and hands-on projects, this training ensures that learners develop practical, job-ready skills in AI application development, model integration, and scalable deployment strategies. Whether you're looking to automate processes, personalize user experiences, or build smart systems, this course provides the essential foundation and advanced strategies you need.
Target Audience
- Software Developers seeking AI integration skills
- Data Scientists transitioning to application development
- Machine Learning Engineers enhancing production skills
- Python Developers expanding into AI-based systems
- Mobile App Developers building intelligent apps
- AI Startups looking to accelerate MVP deployment
- Government and enterprise IT teams building smart applications
Course Objectives
- Understand the fundamentals of artificial intelligence and machine learning
- Explore the Python programming stack for AI development
- Utilize TensorFlow to build and train deep learning models
- Preprocess and manage structured and unstructured data for AI apps
- Design user-centric AI-powered web or mobile applications
- Deploy machine learning models into production environments
- Integrate TensorFlow models into front-end interfaces or APIs
- Optimize model performance and reduce inference latency
- Apply responsible AI practices including fairness and interpretability
- Use cloud platforms and APIs to scale AI applications effectively
Duration
10 Days
Course content
Module 1: Introduction to AI and Machine Learning Concepts
- Supervised, unsupervised, and reinforcement learning
- Neural networks and deep learning basics
- Use cases in finance, healthcare, and smart services
- AI life cycle from ideation to deployment
- Impact of AI on industries and society
Module 2: Python for AI Development
- Python syntax and key libraries (NumPy, Pandas, Matplotlib)
- Data structures and functional programming
- Working with Jupyter notebooks
- Debugging and virtual environments
- Integrating APIs with Python
Module 3: Data Acquisition and Preprocessing
- Importing data from various sources
- Data cleaning and transformation
- Feature engineering and normalization
- Handling missing values and outliers
- Data splitting and pipeline automation
Module 4: TensorFlow Fundamentals
- Computational graph concepts
- Tensors, operations, and sessions
- Building models using TensorFlow 2.x
- Training and evaluating models
- Understanding loss functions and optimizers
Module 5: Deep Learning Model Development
- Building neural networks with Keras API
- CNNs for image recognition
- RNNs for sequential and text data
- Transfer learning techniques
- Evaluating performance with metrics
Module 6: AI Application Architecture Design
- Designing AI-based workflows
- Microservices vs monoliths for AI deployment
- REST API integration for models
- App frameworks for front-end/backend interaction
- End-to-end data flow design
Module 7: Real-Time Inference and Model Deployment
- Saving and loading trained models
- TensorFlow Serving and model serialization
- Building inference pipelines
- Real-time predictions with RESTful APIs
- Edge AI and lightweight deployment
Module 8: Building Web Apps with Flask or FastAPI
- Creating interactive interfaces for model interaction
- Routing, templating, and user input handling
- Model interaction through endpoints
- UI/UX considerations for AI results
- Error handling and logging
Module 9: Using TensorFlow Lite and TensorFlow.js
- Converting models for mobile and browser
- Deploying on Android/iOS devices
- Running models in the browser
- Performance considerations
- Demo integrations with sensors and IoT
Module 10: Performance Tuning and Optimization
- Reducing model size and latency
- Quantization and pruning
- Parallelization and GPU acceleration
- Monitoring resource utilization
- Memory optimization and batch processing
Module 11: Ethical AI and Model Interpretability
- AI bias and fairness assessment
- Explainable AI (XAI) methods
- Building transparency into AI models
- Human-in-the-loop design
- Privacy, consent, and data ethics
Module 12: Scaling AI Applications with Cloud Services
- TensorFlow on Google Cloud and AWS
- Using ML pipelines for CI/CD
- AutoML and managed services
- Monitoring AI in production
- Data versioning and model retraining
Training Approach
This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.
Tailor-Made Course
This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449
Training Venue
The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.
Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant
Certification
Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.
Airport Pickup and Accommodation
Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449
Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 10 working days before commencement of the training.
| Dates | Fees | Location | Apply |
|---|---|---|---|
| 07/07/2025 - 18/07/2025 | $3000 | Nairobi, Kenya |
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| 14/07/2025 - 25/07/2025 | $5500 | Johannesburg, South Africa |
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| 14/07/2025 - 25/07/2025 | $3000 | Nairobi, Kenya |
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| 04/08/2025 - 15/08/2025 | $3000 | Nairobi, Kenya |
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| 11/08/2025 - 22/08/2025 | $3500 | Mombasa, Kenya |
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| 18/08/2025 - 29/08/2025 | $3000 | Nairobi, Kenya |
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| 01/09/2025 - 12/09/2025 | $3000 | Nairobi, Kenya |
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| 08/09/2025 - 19/09/2025 | $4500 | Dar es Salaam, Tanzania |
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| 15/09/2025 - 26/09/2025 | $3000 | Nairobi, Kenya |
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| 06/10/2025 - 17/10/2025 | $3000 | Nairobi, Kenya |
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| 13/10/2025 - 24/10/2025 | $4500 | Kigali, Rwanda |
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| 20/10/2025 - 31/10/2025 | $3000 | Nairobi, Kenya |
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| 03/11/2025 - 14/11/2025 | $3000 | Nairobi, Kenya |
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| 10/11/2025 - 21/11/2025 | $3500 | Mombasa, Kenya |
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| 17/11/2025 - 28/11/2025 | $3000 | Nairobi, Kenya |
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| 01/12/2025 - 12/12/2025 | $3000 | Nairobi, Kenya |
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| 08/12/2025 - 19/12/2025 | $3000 | Nairobi, Kenya |
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