Machine Learning Apis In Web And Mobile Applications Training Course in Kenya
Introduction
The Machine Learning APIs in Web and Mobile Applications Training Course equips developers, data scientists, and tech professionals with the practical skills to integrate machine learning into real-world digital products. As businesses increasingly rely on intelligent automation, predictive analytics, and personalized experiences, the ability to embed pre-trained machine learning models into web and mobile environments is critical for innovation and competitive advantage.
This hands-on course offers comprehensive coverage of integrating cloud-based and custom ML APIs into frontend and backend systems, with a focus on image recognition, natural language processing, recommendation engines, and real-time analytics. Participants will learn to deploy, test, and secure machine learning features in scalable applications using leading platforms such as TensorFlow Serving, AWS, Azure, and Google Cloud ML.
Target Audience
- Web and mobile application developers
- Machine learning engineers and data scientists
- Cloud architects and backend engineers
- Software developers exploring AI integration
- Technical project managers in AI-driven teams
- IT professionals working in product innovation
- DevOps teams managing AI-enabled infrastructure
Course Objectives
- Understand the fundamentals of ML APIs and their role in application development
- Explore various cloud-based and open-source machine learning API services
- Integrate ML APIs into web applications using JavaScript, Python, and REST
- Embed machine learning features in mobile apps using SDKs and cloud APIs
- Handle real-time inference with minimal latency and resource usage
- Secure and manage access to ML APIs in production environments
- Deploy custom models as RESTful endpoints using TensorFlow Serving or FastAPI
- Monitor and evaluate ML API performance and prediction accuracy
- Optimize applications for scalability and cost-efficiency when using ML services
- Build and demo AI-powered apps across web and mobile platforms
Duration
10 Days
Course content
Module 1: Introduction to ML APIs and Deployment Strategies
- Types of ML APIs: vision, NLP, recommendation, prediction
- RESTful principles and gRPC for ML service communication
- Comparing hosted vs custom-deployed ML API options
- Use cases across sectors and platforms
- Setting up API credentials and access control
Module 2: Cloud-Based ML Services Overview
- Exploring Google Cloud ML, AWS SageMaker, and Azure ML
- Using pre-trained APIs for image, speech, and text
- Pricing and performance benchmarking
- SDK integration for mobile and web
- Real-world examples of ML API usage
Module 3: Integrating ML APIs in Web Applications
- Frontend integration using JavaScript and React
- Backend API calls using Python (Flask, FastAPI)
- Handling authentication tokens securely
- Visualizing predictions and feedback loops
- Error handling and response caching strategies
Module 4: Mobile Integration Using ML SDKs and APIs
- ML Kit for Firebase and Core ML for iOS
- Sending images and audio for inference
- Offline vs online inference strategies
- Performance profiling in mobile apps
- Device-specific optimizations
Module 5: Image and Video Recognition with APIs
- Object detection, facial recognition, and OCR
- Use of Google Vision API and AWS Rekognition
- Processing images from camera feeds
- Annotating and storing recognition results
- Building user-facing features with visual AI
Module 6: Natural Language Understanding in Apps
- Sentiment analysis, entity recognition, language detection
- Using Google Natural Language API and Azure Text Analytics
- Chatbot integration and NLP-based search features
- Streaming audio to speech-to-text APIs
- Multilingual support and localization
Module 7: Recommendation Engines and Personalization
- Basics of collaborative filtering and content-based filtering
- Using ML APIs to suggest content or actions
- Real-time vs batch inference scenarios
- Data collection for personalization
- Evaluating recommendation effectiveness
Module 8: Creating and Hosting Custom ML APIs
- Exporting models from TensorFlow, Scikit-learn, or PyTorch
- Deploying models with TensorFlow Serving and FastAPI
- Dockerizing and scaling ML services
- API versioning and lifecycle management
- Exposing endpoints securely
Module 9: Monitoring, Logging, and Analytics
- Logging API calls and usage metrics
- Setting alerts for errors and latency spikes
- Analyzing user interactions with ML-powered features
- Integration with CloudWatch, Stackdriver, or Prometheus
- Dashboarding for stakeholders
Module 10: Security and Governance of ML APIs
- API key management and IP whitelisting
- Rate limiting and quota enforcement
- GDPR and data protection for ML services
- Auditing and activity tracking
- Building responsible AI into applications
Module 11: Real-World Project: AI-Enhanced Web App
- Defining a project scope and selecting APIs
- Building an AI-powered feature set
- Testing and deploying to the cloud
- User experience considerations
- Collecting user feedback for refinement
Module 12: Real-World Project: AI-Enhanced Mobile App
- Setting up mobile SDKs and backend inference
- Managing latency and app responsiveness
- Deploying to app stores or internal testers
- Integrating usage analytics
- Final demo and peer review
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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