Course Outline
Introduction
- Overview of Anaconda features and components
- Core concepts and terminologies
Getting Started
- Installing Anaconda
- Exploring the Anaconda Navigator UI
- Running a Python program
Using Anaconda Navigator
- Creating Python and R environments
- Managing environments, packages, and channels
- Building Anaconda Navigator apps
- Using multiple versions of Python
Managing Packages with Conda
- Configuring Conda
- Managing packages, channels, and virtual packages
- Using Conda with Travis CI
- Conda Python APIs
Data Science, Analysis, and ML in Anaconda
- Python and R fundamentals
- Tools and techniques
- Use cases and examples
- Visualization and analysis
Troubleshooting
Summary and Next Steps
Requirements
- Python programming experience
Audience
- Data scientists
Testimonials (6)
examples and exercises
Kamil
Course - Introduction to Data Science and AI using Python
Machine Translated
All the examples used and the lecturing style was on point even for a begginer i was able to understand and the training was so patient and always willing to go extra mile when in need of assistance.
Mathipa Chepape - Vodacom
Course - Big Data Business Intelligence for Telecom and Communication Service Providers
Intensity, Training materials and expertise, Clarity, Excellent communication with Alessandra
Marija Hornis Dmitrovic - Marija Hornis
Course - Data Science for Big Data Analytics
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
Winnie Chan - Statistics Canada
Course - Jupyter for Data Science Teams
Trainer was accommodative. And actually quite encouraging for me to take up the course.
Grace Goh - DBS Bank Ltd
Course - Python in Data Science
From learning, being able to put the proposed exercises into practice.
Samanta - Imdepa Rolamentos
Course - Qlik Sense for Data Science
Machine Translated