AI Engineer — Artificial Intelligence Engineer

Module 1 · Python for AI (Refresher) · Lesson 1 of 1

Module overview — Python for AI (Refresher)

Module overview — Python for AI (Refresher) Goal : Isolate a project in a virtual environment, clean a dataset with Python and Pandas, and write readable, reproducible code. Study time : Durée d'étude : 6 h Prerequisites : no prerequisites Running thread : Wanjiru, in Nairobi. Wanjiru joins a team in Nairobi that analyses the transactions of a mobile wallet (M-Pesa and Airtel Money). She is handed a raw CSV file and a script that only runs on its author's laptop: libraries clash, the data is messy, and management expects five clear statistics. In this module she learns to isolate her project, clean the data and summarise it with code a colleague can rerun. Lesson plan : 1. Virtual environments and package management 2. Data structures and manipulation 3. NumPy and Pandas essentials 4. Good coding practices for data and AI What you will be able to do : - Isolate a project's dependencies in a virtual environment and pin their versions - Clean a raw dataset with lists, dictionaries and sets - Compute five commented descriptive statistics with Pandas from a CSV file - Document a function with a docstring and type annotations End-of-module questions (Answer in writing, with figures.) : 1. How many packages are listed in your dependency file, and how many are pinned to an exact version? Give both numbers. 2. How many anomalies did you find in your dataset, and how many rows did you remove? Give the numbers. 3. Why do the mean and the median of your amounts differ? Explain in one sentence. Module deliverables : - Your dependency file with pinned versions - Your script or notebook for cleaning and five commented statistics - Your project sheet in the notebook

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