Learn Autonomous Programming with Python

The current industry (also called Industry 4.0) has witnessed an unprecedented expansion of technology in a short span of time, owing to an exponential increase in computational power coupled with internet technology. Consequently, domains like artificial intelligence, machine learning, deep learning and robotic process automation have gained prominence and become the backbone of organizations, making it inevitable for professionals to upgrade their skills in these domains. 

Orchestrate your work with AI and ML. Learn RPA's power, conduct web symphonies, utilize spreadsheets, and automate emails. You can also extract data from PDFs and images, choreograph applications, and play with deep learning. Design workflows, create hyperautomation finales, and combine Python with UiPath. You can further build a solid stage for your projects with PyScript, and continue with test automation. 

This book equips you to revolutionize your work, one Python script at a time. This book can be used as ready to reference as well as a user manual for quick solutions to common organizational needs and even for brushing up on key technical domain concepts.

KEY FEATURES  

• Explore Python commands for RPA, workflows and hyperautomation.
• Concise chapters with lucid examples and elaborate codes that make learning interesting.
• Practical industry use case at the end of every chapter to highlight its real world application.

WHAT YOU WILL LEARN

• You will have a clear understanding of Python and create concise, flexible and maintainable applications for current industry needs.
• You will explore web scraping techniques using powerful libraries to extract valuable data from the web.
• You will have a high level overview of fundamentals in ML, deep learning, RPA, and hyperautomation.
• You will learn to write compact and maintainable code in Python catering to typical applications in contemporary industries. 
• You will also learn how to apply your learnings to real world industry scenarios using the practical Python use cases presented at the end of each chapter.

WHO THIS BOOK IS FOR

This book is specifically meant for students and professionals who have prior working knowledge of Python from a basic to intermediate level and would want to expand their horizon of Python programming.

1. Why Python for Automation?
2. RPA Foundations
3. Getting Started with AI/ML in Python
4. Automating Web Scraping
5. Automating Excel and Spreadsheets
6. Automating Emails and Messaging
7. Working with PDFs and Images
8. Mechanizing Applications, Folders and Actions
9. Intelligent Automation Part 1: Using Machine Learning
10. Intelligent Automation Part 2: Using Deep Learning
11. Automating Business Process Workflows
12. Hyperautomation
13. Python and UiPath
14. Architecting Automation Projects
15. The PyScript Framework
16. Test Automation in Python

In a diverse career spanning 12+ years, across six multinational organizations, Varun P Divadkar holds the distinction of having contributed to a variety of global techno-functional engagements with his delivery expertise in Python programming applications towards cutting edge domains like Artificial Intelligence, Machine Learning, Deep Learning and Robotic Process Automation. Being a qualified Mechanical Engineer with a gold medal from MIT has endowed him with uniquely acquired logical reasoning abilities and quantitative aptitude. This has further enabled him to grasp key mathematical and technical concepts with a steep learning curve and thereby mentor students and professionals in their journey towards exploration of these cutting edge domains.

He began his career with the prestigious Tata group within the manufacturing domain in the engineering services sector and was involved in automation of engineering designs. Thereafter, he had a stint of 5+ years with financial consulting giants Ernst & Young and Deloitte, where he had the privilege to work out of the global financial epicenter of Wall Street, Manhattan, New York and the culturally significant hub of Los Angeles, California. Within India, he has worked across major commercial centers like Mumbai, Bengaluru, Chennai, Hyderabad and Pune, thus adding to his diverse expanse of professional network. Of recent, he has been with three banking organizations and currently leads the Machine Learning and Generative AI initiative at a large global commercial bank as the Vice President.