After doing these courses, I feel confident creating professional visualizations and dashboards
Shoebur RahmanProcurement Specialist, Giz Bangladesh
Course Description
Improve Your Python Skills
Learning Python is crucial for any aspiring data science practitioner. Learn to visualize real data with Matplotlib’s functions and get acquainted with data structures such as the dictionary and pandas DataFrame. This four-hour intermediate course will help you to build on your existing Python skills and explore new Python applications and functions that expand your repertoire and help you work more efficiently.Learn to Use Python Dictionaries and pandas
Dictionaries offer an alternative to Python lists, while the pandas dataframe is the most popular way of working with tabular data. In the second chapter of this course, you’ll find out how you can create and manipulate datasets, and how to access them using these structures. Hands-on practice throughout the course will build your confidence in each area.Explore Python Boolean Logic and Python Loops
In the second half of this course, you’ll look at logic, control flow, filtering and loops. These functions work to control decision-making in Python programs and help you to perform more operations with your data, including repeated statements. You’ll finish the course by applying all of your new skills by using hacker statistics to calculate your chances of winning a bet.Once you’ve completed all of the chapters, you’ll be ready to apply your new skills in your job, new career, or personal project, and be prepared to move onto more advanced Python learning.
Feels like what you want to learn?
Start Course for FreeWhat you'll learn
- Identify and apply Matplotlib functions to create line, scatter, and histogram plots.
- Recognize how to create, update, and manipulate dictionaries and pandas DataFrames.
- Differentiate between comparison, boolean, and logical operators, and assess their use in filtering data.
- Identify the use of loops (for, while) and apply them to iterate over lists, dictionaries, NumPy arrays, and pandas DataFrames.
- Evaluate random number generation and simulations (random walks, distributions) to analyze probabilities and outcomes.
Prerequisites
Curriculum
Course outline
1
Matplotlib
Data visualization is a key skill for aspiring data scientists. Matplotlib makes it easy to create meaningful and insightful plots. In this chapter, you’ll learn how to build various types of plots, and customize them to be more visually appealing and interpretable.
- Basic plots with Matplotlib50 XP
- Line plot (1)100 XP
- Line Plot (2): Interpretation50 XP
- Line plot (3)100 XP
- Scatter Plot (1)100 XP
- Scatter plot (2)100 XP
- Histogram50 XP
- Build a histogram (1)100 XP
- Build a histogram (2): bins100 XP
- Build a histogram (3): compare100 XP
- Choose the right plot (1)50 XP
- Choose the right plot (2)50 XP
- Customization50 XP
- Labels100 XP
- Ticks100 XP
- Sizes100 XP
- Colors100 XP
- Additional Customizations100 XP
- Interpretation50 XP
2
Dictionaries & Pandas
Learn about the dictionary, an alternative to the Python list, and the pandas DataFrame, the de facto standard to work with tabular data in Python. You will get hands-on practice with creating and manipulating datasets, and you’ll learn how to access the information you need from these data structures.
3
Logic, Control Flow and Filtering
Boolean logic is the foundation of decision-making in Python programs. Learn about different comparison operators, how to combine them with Boolean operators, and how to use the Boolean outcomes in control structures. You'll also learn to filter data in pandas DataFrames using logic.
4
Loops
There are several techniques you can use to repeatedly execute Python code. While loops are like repeated if statements, the for loop iterates over all kinds of data structures. Learn all about them in this chapter.
5
Case Study: Hacker Statistics
This chapter will allow you to apply all the concepts you've learned in this course. You will use hacker statistics to calculate your chances of winning a bet. Use random number generators, loops, and Matplotlib to gain a competitive edge!
Intermediate Python
Course
Complete
