🔎 Topics covered in this course:
-
Independent Work Tasks
-
Learn to Code – on real data (16 PDF files to chart)
-
A brief overview of the data in the task
Introduction
Part 1. Python. 1st Dataset. PDF files. Tika OCR. Regular Expression. Array und Function
1st Dataset. PDF files. Tika OCR. Extracting content and metadata.00:08:40
Regular Expression in Python. Pattern matching in Python with RegEx.00:10:33
Array und Function in Python. Add data to Array. Create function.00:09:48
Python & Regular Expressions
Part 1. Pandas DataFrame. Kaggle. Jupiter Notebook.
Pandas DataFrame. Two-dimensional size-mutable, tabular data structure.00:09:15
Pandas & Kaggle
Part 1. Independent Work Tasks. 2nd Dataset.
2nd Dataset. My solution.00:05:39
Part 1. GitHub. Desktop GitHub
GitHub. Desktop GitHub. Store and manage code00:07:03
Part 2. Python. PyTesseract OCR. Regular Expression. Array und Function.
Scanned PDF files. Convert a pdf document to images using Python.00:10:49
Installing Tesseract. User-defined functions in Python00:09:04
Python & Regular Expressions
Part 2. RegEx. Regular Expression in Python.
Array und Function in Python. Add data to Array.00:13:21
GeoPy – easy to locate the coordinates. Get the latitude and longitude of location00:08:52
Part 2. Kaggle. Jupyter Notebook.
Kaggle. Jupiter Notebook. Plot data with matplotlib, seaborn, squarify.00:10:58
Folium. Mapping in Python. Plot Geographic Data on a Map.00:08:56
Part 3. Big Data Storage and MySQL.
Big Data Storage. Three ways to store digital data.00:05:23
MySql. SQL. Introduction. How it works?00:03:45
Part 3. Practice. Export Excel worksheet data to a MySQL table
Installing and Launching MySQL Workbench. How to Get Started with MySQL Workbench00:03:29
Practice. Excel table into MySql. Import Excel data into a MySQL database.00:08:16
MySQL Quiz
Part 3. A Storage System for Big Data. Hadoop.
Spark. Hadoop. Data’s Distribution. A Storage System for Big Data.00:03:41
Part 3. Practice. How Apache Spark makes your slow MySQL queries 10x faster.
Installing and Launching Apache Spark. Download and Get Started.00:05:07
Practice. Connecting Python To The Spark. Get Started with PySpark and Jupyter Notebook00:07:11
Practice. Connecting MySQL with Spark. Export Data from Mysql to Spark.00:09:33
Spark and Hadoop Quiz
Part 4. The Data Visualisation Tools. Introduction
Data Visualization Tools. Power BI, Tableau, Google Data Studio, Jupyter.00:04:57
Part 4. Practice. Data Visualization with Python. Kaggle and Jupyter Notebook.
Python Data Visualizations. Prepare Data for Visualizations. (Part 1/3)00:11:10
Python Data Visualizations. Clean data for Visualizations (Part 2/3).00:04:57
Python Data Visualizations. Data Visualizations in Jupyter Notebook (Part 3/3).00:11:19
Plotting in Python Quiz
Part 4. Online Data Visualization Tools. Introduction and getting started.
Practice. Power BI. Introduction and getting started.00:07:00
Practice. Tableau. Introduction and getting started.00:04:35
Practice. Google Data Studio. Introduction and getting started.00:06:20
Part 5. Machine Learning. An Introduction.
What is machine learning? Key ML Terminology.00:06:45
Practice. Predict the price of houses. Dataset 1. Beginner’s Guide to Jupyter00:10:24
Part 5. Practice. How does machine learning work?
How does machine learning work? Prediction of construction time and cost.00:07:13
Practice. Prediction of price and time. Data upload and preparation (Part 1/2)00:08:57
Practice. Prediction of price and time. Evaluation Metrics (Part 2/2)00:10:40
Machine Learning Quiz
Part 5. Workflow of a Machine Learning project.
Workflow of a Machine Learning project. Stages of the Machine Learning Modeling00:05:11
Part 5. Practice. San Francisco – explore Building Permits Data. Build Predictive Model.
Practice. Data loading and preparation to Analyzing (Part 1/2).00:12:32
Practice. Cost Prediction. Way to build a Predictive Model (Part 2/2).00:14:08
Subscribe Newsletter
Connect
Contact
Artem Boiko
- Email: boikoartem@gmail.com
