Part 1. Python. 1st Dataset. PDF files. Tika OCR. Regular Expression. Array und Function

Part 1. Pandas DataFrame. Kaggle. Jupiter Notebook.

Part 1. Independent Work Tasks. 2nd Dataset.

Part 1. GitHub. Desktop GitHub

Part 2. Python. PyTesseract OCR. Regular Expression. Array und Function.

Part 2. RegEx. Regular Expression in Python.

Part 2. Kaggle. Jupyter Notebook.

Part 3. Big Data Storage and MySQL.

Part 3. Practice. Export Excel worksheet data to a MySQL table

Part 3. A Storage System for Big Data. Hadoop.

Part 3. Practice. How Apache Spark makes your slow MySQL queries 10x faster.

Part 4. The Data Visualisation Tools. Introduction

Part 4. Practice. Data Visualization with Python. Kaggle and Jupyter Notebook.

Part 4. Online Data Visualization Tools. Introduction and getting started.

Part 5. Machine Learning. An Introduction.

Part 5. Practice. How does machine learning work?

Part 5. Workflow of a Machine Learning project.

Part 5. Practice. San Francisco – explore Building Permits Data. Build Predictive Model.

Kaggle. Jupiter Notebook. Create an account. Plotting with matplotlib and seabor

📚 Additional materials on topics covered in the course:

Kaggle. The Beginner’s Guide

Jupyter Notebook: An Introduction

Delete rows/columns from DataFrame using Pandas.drop()

Simple Scatter Plots

🔎 Topics covered in this course:

  • How do I upload a file to kaggle kernel?

  • How do you use kaggle dataset?

  • How to run Jupyter notebook using Kaggle kernels?

  • How to convert a CSV to dataframe in Python Jupyter Notebook?

  • How to use the functions of Pandas Dataframe?

  • How do I change the date format of a column in pandas?

  • How do I convert a string to datetime Objects in Python?

  • How to Calculate Difference Between Two Dates in Pandas Dataframe?

  • How do I delete a column in pandas DataFrame?

  • How do I add columns in  pandas DataFrame?

  • How do you visualize a dataset?

  • How do you plot a DataFrame in pandas?