Expert insights, technical tutorials, and real-world case studies from the UK's leading Python development team. Learn from our experience building scalable applications and AI-powered solutions.
Learn how we architect Django applications that handle millions of requests while maintaining performance and security. This comprehensive guide covers everything from database optimization to deployment strategies used in our UK client projects.
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AI Integration
Step-by-step guide to building intelligent chatbots and content generation systems using OpenAI's API with Django. Includes authentication, rate limiting, and cost optimization strategies.
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Django Tutorial
Comprehensive comparison of Django and FastAPI based on our experience building applications for UK businesses. Performance benchmarks, use cases, and migration strategies included.
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Case Study
Real-world case study of how we built an intelligent inventory management system for a UK e-commerce client, resulting in massive cost savings and efficiency improvements.
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Python Tutorial
Complete guide to building high-performance REST APIs using FastAPI. Covers authentication, documentation, testing, and deployment strategies specific to UK compliance requirements.
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AI Case Study
How we developed an AI-powered patient management system that improved efficiency by 40% while maintaining strict GDPR compliance and NHS digital standards.
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Django Advanced
Advanced techniques for optimizing Django applications based on our experience scaling platforms like Core Freight. Database optimization, caching strategies, and infrastructure tips.
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Python Security
Essential security practices for Python applications handling sensitive business data. GDPR compliance, encryption, authentication, and vulnerability prevention techniques.
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Machine Learning
Complete guide to building machine learning models for business predictions using Python, scikit-learn, and TensorFlow. Includes real examples from UK retail and logistics.
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Success Story
How Core Freight transformed their logistics operations using Python automation, reducing processing time by 80% and improving accuracy to 99.9%.
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