Python Language Complete
Become proficient in Python from fundamentals through web development, data analytics, and machine learning.
Get Course Info
Audience: Developers / Architects
Duration: 10 days
Format: Lectures and hands-on labs (50% lecture, 50% lab)
Overview
Python has recently become the most popular language. It excels at data science, artificial intelligence, and many other tasks, but is also outstanding for web and service programming and general application development. This complete course helps beginners become comfortable with Python basics, then takes them through analytics, application development, and machine learning with SciKit-Learn.
Objective
Become proficient in Python from fundamentals through web development, data analytics, and machine learning.
What You Will Learn
- Introducing Python Language
- Intermediate Python Language
- Web Programming
- Database Programming
- Data Analysis
- Visualization
- Deployment
- Machine Learning and AI concepts
Course Details
Audience: Developers / Architects
Duration: 10 days
Format: Lectures and hands-on labs (50% lecture, 50% lab)
- Background with Unix or Linux command line
- Knowledge of a programming language such as Java, C#, or Node.js
Setup: A modern laptop or desktop · Unrestricted Internet · Chrome browser · SSH client
Detailed Outline
- Installing Python
- Python Versions
- IDEs
- Jupyter Notebook
- Data Types
- NumPy
- Packages
- Pandas
- Classes
- Modules / Packages
- Python Packages
- Data Types
- DataFrames
- Schema inferences
- Data exploration
- Database Connectivity
- Pandas and DB
- ORM
- Python Web Frameworks
- Flask
- Restful API with Flask
- Matplotlib
- Seaborn
- Statsmodels
- Making Your Own Packages
- Deployment
- Environments
- How to use Containers with Python
- Dockerizing Python
- Writing C Modules
- Using Python with Other Languages
- TDD and Python
- Unit test Frameworks
- Jupyter notebooks
- Pandas Series and DataFrames
- NumPy & SciPy
- Visualizing Data with Matplotlib
- Introducing Scikit-Learn
- Clustering Data
- Building a Classifier
- Introduction to Spark, PySpark, and Databricks
- Using the Spark framework for Big Data
- Using MLlib for Data Science in PySpark
- Geolocation Data
- Packet Analysis
Ready to Get Started?
Contact us to learn more about this course and schedule your training.