After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
Begin your journey into Data Science! Even if you've never written a line of code in your life, you'll be able to follow this course and witness the power of Python to perform Data Science. You'll use data to solve the mystery of Bayes, the kidnapped Golden Retriever, and along the way you'll become familiar with basic Python syntax and popular Data Science modules like Matplotlib (for charts and graphs) and pandas (for tabular data).
Feels like what you want to learn?
Start Course for FreeWhat you'll learn
- Differentiate line, scatter, bar, and histogram plotting functions in matplotlib, including the positional and keyword arguments each requires
- Distinguish between bracket and dot notation when selecting columns or rows in a pandas DataFrame based on given code examples
- Evaluate sample visualization code to assess whether axis labels, legends, styles, and other annotations are correctly applied to convey information
- Identify valid Python statements for importing modules, defining variables, and executing functions in a DataCamp environment
- Recognize pandas commands that load CSV files into DataFrames and reveal key dataset attributes using head and info methods
Prerequisites
There are no prerequisites for this course
Curriculum
Course outline
1
Getting Started in Python
Welcome to the wonderful world of Data Analysis in Python! In this chapter, you'll learn the basics of Python syntax, load your first Python modules, and use functions to get a suspect list for the kidnapping of Bayes, DataCamp's prize-winning Golden Retriever.
- Dive into Python50 XP
- Importing Python modules100 XP
- Correcting a broken import100 XP
- Creating variables50 XP
- Creating a float100 XP
- Creating strings100 XP
- Correcting string errors100 XP
- Valid variable names50 XP
- Fun with functions50 XP
- Load a DataFrame100 XP
- Correcting a function error100 XP
- Snooping for suspects100 XP
2
Loading Data in pandas
In this chapter, you'll learn a powerful Python libary: pandas. pandas lets you read, modify, and search tabular datasets (like spreadsheets and database tables). You'll examine credit card records for the suspects and see if any of them made suspicious purchases.
3
Plotting Data with Matplotlib
Get ready to visualize your data! You'll create line plots with another Python module: Matplotlib. Using line plots, you'll analyze the letter frequencies from the ransom note and several handwriting samples to determine the kidnapper.
4
Different Types of Plots
In this final chapter, you'll learn how to create three new plot types: scatter plots, bar plots, and histograms. You'll use these tools to locate where the kidnapper is hiding and rescue Bayes, the Golden Retriever.
Introduction to Data Science in Python
Course
Complete
