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Introduction

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.

Regular Expression in Python. Pattern matching in Python.

📚 Additional materials on topics covered in the course:

Python For Loops
https://www.w3schools.com/python/python_for_loops.asp

Regular expression operations
https://docs.python.org/2/library/re.html

Regular Expressions Quick Start
https://www.regular-expressions.info/quickstart.html

🔎 Topics covered in this course:

• What is regular expression?

• How do you match in regex?

• Online RegEx tester and debugger.

• Use Findall in Python?

• Using Regex for Text Manipulation in Python.

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