The book "Starting Data Analytics with Generative AI and Python" by Artur Guja is a practical guide to mastering modern data analytics methods using Generative AI — including LLMs (Large Language Models), AutoML, and Python-based AI tools.
Generative AI is transforming data analysis by automating information processing, prediction, and the construction of complex analytical models. Python, the go-to language in Data Science, offers powerful libraries for data manipulation and seamless AI model integration.
Download "Starting Data Analytics with Generative AI and Python" in PDF to learn how to use Generative AI for automating workflows, building analytical models, and optimizing processes.
Why is this book essential?
Generative AI enables you to:
- Analyze large datasets faster and more accurately
- Automate routine analytics and ML tasks
- Create predictive models with neural architectures
- Optimize business processes and simplify the handling of textual and visual data
This book equips analysts, developers, and data professionals with practical tools to apply Generative AI to real-world challenges.
Who should read "Starting Data Analytics with Generative AI and Python"?
- Data analysts and BI professionals: Automate data processing and forecasting using AI
- Python developers and data engineers: Learn Python libraries, work with ChatGPT, LLaMA, Bard APIs, and integrate AI into ETL pipelines
- Business analysts and marketers: Use Generative AI for client data analysis, reporting automation, and market forecasting
- Students and researchers: Apply ML, AI, and AutoML in academic or scientific projects
More About the Author of the Book
The Developer's Opinion About the Book
A practical starter guide that shows how to enhance analytics workflows using Python and generative AI. It covers data storytelling, automation of reports, and AI-assisted EDA. After reading, you’ll speed up insights and simplify communication in your analytics projects. Great for analysts and early-career data scientists. It introduces tools like Pandas Profiling and ChatGPT APIs to make exploratory analysis faster, more visual, and highly reproducible.
Sarah Bennett, Machine Learning Developer
FAQ for "Starting Data Analytics with Generative AI and Python"
Which Generative AI models are covered in the book?
Artur Guja discusses GPT-4, LLaMA, Bard, Claude, and shows how to integrate them into Python apps using APIs and local LLMs.
Which Python tools are used for analytics?
The book covers pandas, NumPy, Matplotlib, seaborn, scikit-learn, as well as LangChain, OpenAI API, and Hugging Face Transformers.
Can this book be used with corporate datasets?
Yes — it includes business use cases such as financial analytics, marketing predictions, and report automation using Generative AI.
How does Generative AI assist in Data Science?
These models handle large data volumes, summarize reports, generate forecasts, and automatically build analytical dashboards.
Do you need prior ML knowledge to follow this book?
Basic Python and data analysis knowledge is recommended, but the book offers a practical introduction to ML and AutoML concepts.
Information
| Author: | Artur Guja, Marlena Siwiak, Marian Siwiak | Language: | English |
| Publisher: | Manning | ISBN-13: | 978-1633437210 |
| Publication Date: | November 19, 2024 | ISBN-10: | 1633437213 |
| Print Length: | 360 pages | Category: | Machine Learning and Artificial Intelligence Books |
Get PDF version of "Starting Data Analytics with Generative AI and Python" by Artur Guja, Marlena Siwiak, Marian Siwiak
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