Code Factory: Navigating the wonders beyond binary brilliance: 100+ Programming Solutions

Beginners in the programming world often wander to get some essential books to learn logic building with the help of algorithms, flowcharts, and minor C/Python language code. Addressing this demand, the book features over 100 solved programming questions thoughtfully arranged in incremental order of difficulty. The main objective of the book is to trigger and nurture logic-building skills among the students.

The book is structured to introduce concepts gradually, ensuring a smooth learning curve. This guide gets you ready for any programming challenge, starting from simple input/output to tackling complex problem-solving. Learn decision-making with if-else, automate with loops, and understand logic using Python and C examples. Master algorithms, flowcharts, and creative thinking. Apply your skills to real-world problems and turn them into solutions.

This book will help the readers develop a well-rounded skill set covering flowcharts, algorithmic thinking, and practical implementation in both C and Python languages. It will provide a holistic foundation for anyone aspiring to become proficient in coding.

Key Features

• The book's step-by-step approach helps students develop logic skills gradually.
• Learn about flowcharts and algorithms for a clearer understanding of logic.
• Explore two programming languages to boost confidence and overcome fear of coding.

What you will learn

• Learn programming comprehensively, from basics to advanced levels.
• Translate problem-solving methods into systematic flowcharts.
• Build a solid foundation in algorithmic design and problem-solving.
• Master intermediate and advanced programming techniques.
• Gain hands-on coding experience in C and Python languages.

Who this book is for

The book is tailored for entry-level college and university students eager to learn coding skills. The book is also beneficial for students and self-learners eager to crack the code to effective problem-solving.

About the Author

Shikha Jain is an Assistant Professor at Jaypee Institute of Information Technology (JIIT), NOIDA, INDIA. She has more than twenty years of research and academic experience. She has received her PhD in computer science from Jaypee Institute of Information Technology, Noida, India. She has contributed significantly to the field, publishing numerous research papers in prestigious journals and conferences.

She was a guest editor for the notable Advances in Computational Intelligence and its Applications issue in the International Journal of Information Retrieval Research. She is an active reviewer of many International Journals and a technical program committee member of various International Conferences. Her research area includes

Affective Computing, Emotion Modelling, Cognitive Affective Architectures, Machine Learning, and Soft Computing. She also takes on the editor role for the book Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach.

Kavita Pandey is an Assistant Professor (Senior Grade) at Jaypee Institute of Information Technology (JIIT), Noida. She has more than 20 years of academic experience. She received her B.Tech. in Computer Science and Engineering from M.D. University in 2002 and M.Tech. (CS) from Banasthali Vidyapeeth University in 2003. She obtained her Ph.D. (CS) from JIIT, Noida, India, in January 2017. Presently, she is guiding two Ph.D. students. She has mentored 16 M.Tech. thesis/industrial projects and 57 + undergraduate projects.

She is an editor of a book named Artificial Intelligence, Machine Learning, and Mental Health in Pandemics: A Computational Approach. She has published one patent. She also contributed to IGNOU study material titled Data Communications and Computer Network. Her research interests include Soft Computing, Machine Learning, Vehicular Ad hoc Networks, the Internet of Things, and Optimization Techniques. She has published 60+ articles in International journals and conferences, including Wiley, IEEE, Springer, Inderscience, etc. She was a guest editor of the special issue Advances in Computational Intelligence and Applications in the International Journal of Information Retrieval Research (IJIRR), IGI Global, ESCI, and Web of Science. She is working as an Academic Editor on the Editorial Board of the International Journal of Distributed Sensor Networks, Hindawi. She was a reviewer in many international journals of renowned publishers, including Elsevier, Inderscience, and IEEE Access, among others. She is an active TPC member of many conferences, such as FSDM, REDSET, IC3, UPCON, TEAMC, ICTCS, and many more. She is also a senior member of the IEEE Society.