Data-Scientist-with-Python

Data Camp Track

01 - Introduction to Python

1. Python Basics
2. Python Lists
3. Functions and Packages
4. NumPy

01 - Course

01 - Assignments

02 - Intermediate Python

1. Matplotlib
2. Dictionaries & Pandas
3. Logic, Control Flow and Filtering
4. Loops
5. Case Study: Hacker Statistics

02 - Course

02 - Assignments

03 - Investigating Netflix Movies and Guest Stars in The Office

03 - About the project

Project notebook

04 - Data Manipulation with pandas

1. Transforming DataFrames
2. Aggregating DataFrames
3. Slicing and Indexing DataFrames
4. Creating and Visualizing DataFrames

04 - Course

04 - Assignments

05 - Joining Data with pandas

1. Data Merging Basics
2. Merging Tables With Different Join Types
3. Advanced Merging and Concatenating
4. Merging Ordered and Time-Series Data

05 - Course

05 - Assignments

06 - Introduction to Statistics in Python

1. Summary Statistics
2. Random Numbers and Probability
3. More Distributions and the Central Limit Theorem
4. Correlation and Experimental Design

06 - Course

06 - Assignments

07 - The GitHub History of the Scala Language

07 - About the project

Project notebook

08 - Introduction to Data Visualization with Matplotlib

1. Introduction to Matplotlib
2. Plotting time-series
3. Quantitative comparisons and statistical visualizations
4. Sharing visualizations with others

08 - Course

08 - Assignments

09 - Introduction to Data Visualization with Seaborn

1. Introduction to Seaborn
2. Visualizing Two Quantitative Variables
3. Visualizing a Categorical and a Quantitative Variable
4. Customizing Seaborn Plots

09 - Course

09 - Assignments

10 - Introduction to NumPy

1. Understanding NumPy Arrays
2. Selecting and Updating Data
3. Array Mathematics!
4. Array Transformations

10 - Course

10 - Slides

10 - Assignments

11 - Python Data Science Toolbox (Part 1)

1. Writing your own functions
2. Default arguments, variable-length arguments and scope
3. Lambda functions and error-handling

11 - Course

11 - Assignments

12 - The Android App Market on Google Play

12 - About the project

Project notebook

13 - Python Data Science Toolbox (Part 2)

1. Using iterators in PythonLand
2. List comprehensions and generators
3. Bringing it all together!

13 - Course

13 - Assignments

14 - Intermediate Data Visualization with Seaborn

1. Seaborn Introduction
2. Customizing Seaborn Plots
3. Additional Plot Types
4. Creating Plots on Data Aware Grids

14 - Assignments

15 - Data Communication Concepts

1. Storytelling with Data
2. Preparing to communicate the data
3. Structuring written reports
4. Building compelling oral presentations

15 - Course

18 - Introduction to Importing Data in Python

1. Introduction and flat files
2. Introduction to Importing Data in Python
3. Working with relational databases in Python

18 - Course 18 - Assignments