Module Assessment

Overview

Congrats! You've now completed the first module! You've learned what data science is and where it fits in the broader technology landscape, how to use Google Colab and Jupyter Notebooks to write and run code, how to save your work to GitHub and understand the commit workflow, and how to use AI coding assistants effectively and responsibly. This assessment asks you to demonstrate all of those skills by completing a structured notebook and submitting it to GitHub.

Complete the assessment using this Colaboratory notebook.

Learning Objectives

By the end of this assessment, you will have demonstrated the ability to:

• Demonstrate basic understanding of data science concepts, environment setup, and collaboration tools.
• Validate readiness to move on to Python fundamentals.

Assessment Overview

This assessment has two parts:

1. Coding Assessment — a structured Colab notebook with four tasks to complete
2. Knowledge Check — three conceptual questions to answer in markdown cells

There is no Python data science code in this assessment — this module was about concepts and tools. What you're demonstrating is that your environment works, you understand the workflow, and you can think clearly about what you've learned.

Coding Assessment

Complete the following tasks in a single Colab notebook. Each task includes instructions; complete them in order. When finished, save the notebook to your GitHub repository and submit the link.

Task 1: Environment Verification

In a code cell, run the following and confirm all lines execute without error:

import sys
import pandas as pd
import numpy as np
import matplotlib
import sklearn

print(f"Python:       {sys.version.split()[0]}")
print(f"pandas:       {pd.__version__}")
print(f"numpy:        {np.__version__}")
print(f"matplotlib:   {matplotlib.__version__}")
print(f"scikit-learn: {sklearn.__version__}")
print("\nEnvironment ready!")

Expected output: All five library versions printed without error.

Task 2: Markdown Cell — Data Science in Your Own Words

Add a markdown cell and write a short explanation (3–5 sentences) that answers:

• What is data science, in your own words?
• Name one industry (e.g., healthcare, finance, retail) and describe one specific way data science is used there.
• What do you personally hope to build or analyze by the end of this curriculum?

Your answer should be original — do not copy the lesson text. Use the markdown cell to format your response with a heading and bullet points.

Task 3: Python Basics Check

In a code cell, complete the following without using AI assistance for the actual answers (you may use it to check your work):

# 1. Create a variable called 'my_name' and assign it your name as a string
my_name = ___

# 2. Create a variable called 'birth_year' and assign it your birth year as an integer
birth_year = ___

# 3. Calculate your approximate age and store it in 'my_age'
my_age = ___

# 4. Print a sentence using an f-string: "My name is X and I am approximately Y years old."
print(___)

# 5. Create a list called 'ds_tools' containing at least 4 tools from this module
ds_tools = ___

# 6. Print the number of tools in your list using len()
print(___)

This is not a trick — the goal is to verify that you can write basic Python expressions and that your notebook runs correctly.

Task 4: GitHub Workflow

1. Save this completed notebook to your GitHub repository using File → Save a copy in GitHub
2. Use a descriptive commit message such as "Complete Module 1 assessment" (not "update" or "save")
3. Navigate to your repository on GitHub and confirm the notebook appears there with your commit message
4. In a markdown cell in your notebook, paste the URL of the notebook file on GitHub (it will look like https://github.com/yourname/repo/blob/main/module1_assessment.ipynb)

Task 5: Responsible AI Use

In a markdown cell, briefly answer (2–3 sentences each):

1. You're stuck on a data cleaning error and have been debugging for 20 minutes. How would you use an AI assistant to help, and what would you do after it gives you a response?

2. Your instructor assigns a graded notebook exercise. What is the appropriate way to use AI tools while completing it?

These are open-ended reflection questions — there are no trick answers. Thoughtful, honest responses earn full credit.

Grading Rubric

Submission

1. Save your completed notebook to GitHub using File → Save a copy in GitHub
2. Copy the URL of the notebook file on GitHub
3. Submit the URL to the AI Grader

Knowledge Check