{"product_id":"new-product-13","title":"Python for Data \u0026 AI: The Complete Hands-On Masterclass","description":"\u003cp style=\"hyphenate-character: '-' !important; color: rgb(0, 0, 0); font-family: 'Times New Roman'; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\"\u003e\u003cstrong style=\"hyphenate-character: '-' !important;\"\u003eLearn Python by building the real thing.\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003e\u003cem style=\"hyphenate-character: '-' !important;\"\u003ePython for Data \u0026amp; AI: The Complete Hands-On Masterclass\u003c\/em\u003e\u003cspan\u003e \u003c\/span\u003etakes you from Python foundations to working data pipelines and machine-learning models — every concept paired with runnable code you can adapt to your own projects.\u003c\/p\u003e\n\u003cp style=\"hyphenate-character: '-' !important; color: rgb(0, 0, 0); font-family: 'Times New Roman'; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\"\u003eYou'll start with the Python skills that matter for data work, then master the core stack:\u003cspan\u003e \u003c\/span\u003e\u003cstrong style=\"hyphenate-character: '-' !important;\"\u003eNumPy\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor numerical computing at scale,\u003cspan\u003e \u003c\/span\u003e\u003cstrong style=\"hyphenate-character: '-' !important;\"\u003epandas\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor data wrangling and analysis, and\u003cspan\u003e \u003c\/span\u003e\u003cstrong style=\"hyphenate-character: '-' !important;\"\u003eMatplotlib and Seaborn\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003efor visualisation. From there you'll put\u003cspan\u003e \u003c\/span\u003e\u003cstrong style=\"hyphenate-character: '-' !important;\"\u003escikit-learn\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003eto work on real machine-learning workflows — training, evaluation, hyperparameter tuning, and model interpretation — before pulling everything together in an end-to-end, real-world data project.\u003c\/p\u003e\n\u003cp style=\"hyphenate-character: '-' !important; color: rgb(0, 0, 0); font-family: 'Times New Roman'; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\"\u003eFully current for the modern toolchain — Python 3.14, NumPy 2.4, pandas 3.0 (Copy-on-Write on by default), Matplotlib 3.10, and scikit-learn 1.9 — the book closes with a glossary, package-version setup notes, quick-reference cheat sheets, and further-reading appendices.\u003c\/p\u003e\n\u003cp style=\"hyphenate-character: '-' !important; color: rgb(0, 0, 0); font-family: 'Times New Roman'; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\"\u003e\u003cstrong style=\"hyphenate-character: '-' !important;\"\u003eYou will learn to:\u003c\/strong\u003e\u003cspan\u003e \u003c\/span\u003e- Write clean, idiomatic Python for data work — functions, iteration, file and data formats - Compute at scale with NumPy arrays and vectorisation - Load, clean, reshape, and analyse data with pandas DataFrames - Build clear, publication-quality charts with Matplotlib and Seaborn - Train, evaluate, tune, and interpret models with scikit-learn - Assemble a complete, real-world data pipeline from raw data to results\u003c\/p\u003e\n\u003cp style=\"hyphenate-character: '-' !important; color: rgb(0, 0, 0); font-family: 'Times New Roman'; font-size: medium; font-style: normal; font-variant-ligatures: normal; font-variant-caps: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: start; text-indent: 0px; text-transform: none; widows: 2; word-spacing: 0px; -webkit-text-stroke-width: 0px; white-space: normal; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;\"\u003eWhether you're starting out or sharpening your toolkit, this hands-on masterclass gets you building fast.\u003c\/p\u003e\n\u003cp\u003e \u003c\/p\u003e","brand":"Professional Developer Store","offers":[{"title":"Default Title","offer_id":58295591305548,"sku":null,"price":4.25,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0849\/7728\/7500\/files\/PythonforDataandAI-Cover_front_6.93x9.84.png?v=1785849601","url":"https:\/\/professionaldeveloper.store\/products\/new-product-13","provider":"Professional Developer Store","version":"1.0","type":"link"}