AI-assisted Programming for Web and Machine Learning

Artificial intelligence is redefining how software is created, enabling developers to code faster, improve accuracy, and bring innovative ideas to life. In today’s competitive technology landscape, AI-assisted programming is no longer optional; it’s a core skill for building modern web applications and machine learning solutions.

This book systematically guides you through the whole development cycle. You will start with the foundations of understanding AI-assisted programming, setting up your environment, and mastering prompt engineering. You will then discover how AI can accelerate front end and back end web development, enhance debugging, and optimize performance. You will also explore data preprocessing, model creation, training, and deploying optimized solutions with the help of real-world examples, case studies, and hands-on exercises, ensuring you can apply every concept in practice. Also, by mastering prompt engineering, you will be able to generate, debug, and optimize code across both these high-demand fields.

By the end of this book, you will have the confidence and skills to integrate AI into your workflow, automate time-consuming tasks, build intelligent applications, and deliver impactful, future-ready solutions.

WHAT YOU WILL LEARN
● Apply prompt engineering effectively for web and ML projects.
● Develop AI-powered front end and back end applications efficiently.
● Automate debugging, testing, and performance optimization with AI.
● Integrate AI tools seamlessly into full-stack development workflows.
● Train, fine-tune, and deploy scalable ML models in the cloud.
● Understand AI-assisted programming concepts and set up development tools.
● Preprocess data and create AI-driven machine learning pipelines.

WHO THIS BOOK IS FOR
This book is for learners who want to explore the power of AI-assisted programming in web development and machine learning. Software engineers, web developers, and data scientists who possess foundational programming skills, ideally with Python or JavaScript, can also use it to upgrade their skills.

1. AI in Programming
2. Setting up Your AI Environment
3. Prompt Engineering
4. AI in Front end Development
5. AI for Back end Development
6. Debugging and Optimization with AI
7. Data Preprocessing with AI
8. Building and Training Machine Learning Models
9. Deploying Optimized ML Models
10. Real-world Applications
11. Future Innovations and Ethics in AI

● Dr. Muralidhar Kurni is an accomplished educator, author, researcher, and entrepreneurship trainer with more than 25 years of experience in teaching and academic leadership. He is currently an associate professor in the department of computer science and engineering at Anantha Lakshmi Institute of Technology and Sciences (Autonomous), Ananthapuramu, India. He holds a Ph.D. in computer science and engineering from JNTUA, India, and has completed postdoctoral research at the University of South Florida, USA. An IEEE senior member, Dr. Kurni has authored and edited several books with leading international publishers and published extensively in reputed journals and conferences in areas including AI, IoT, cloud computing, and blockchain. Recognized with multiple national and international awards for excellence in teaching, research, and innovation, he also serves on editorial boards and reviews for prestigious scientific publications.

● Ramesh Krishnamaneni is a seasoned technology professional with over 17 years of expertise in hybrid and multi-cloud architectures (IBM, AWS, Azure), high performance computing (HPC), artificial intelligence (AI), and quantum computing. He is currently a solutions architect – cloud center of excellence at IBM, leading enterprise-level cloud transformation projects, designing hybrid cloud strategies, and mentoring global teams. Ramesh holds an M.S. in software systems from BITS Pilani, a B.E. in electrical and electronics engineering from JNTU Anantapur, and has completed a postgraduate specialization in artificial intelligence and machine learning from the University of Texas at Austin. He has co-authored several international journal and conference publications in AI, machine learning, IoT, and big data analytics. A holder of multiple IBM certifications, as well as patents, he has been recognized with numerous innovation and excellence awards for his contributions to technology, research, and professional leadership.

● Dr. Srinivasa K.G. is a distinguished academician with over two decades of experience in teaching, research, and academic leadership. He currently serves as professor of data science and artificial intelligence and dean (academics) at DSPM IIIT-Naya Raipur, India. He holds a Ph.D. in computer science and engineering from Bangalore University, is a CMI Level 5 awardee in management and leadership, and a BOYSCAST Fellow of the department of science and technology, Government of India. Dr. Srinivasa has authored numerous books and over 150 research papers in reputed international journals and conferences, with expertise spanning data mining, cloud computing, IoT, learning analytics, and cyber-physical systems. He has held prestigious academic and research positions in India and abroad, including post-doctoral research at the University of Melbourne, Australia. A senior member of IEEE and ACM, he has received multiple national and international awards recognizing his outstanding contributions to engineering education and research.