Python for Data Science Essential Training Part 1
4.0 /5- Offered byLinkedin Learning
Python for Data Science Essential Training Part 1 at Linkedin Learning Overview
Duration | 6 hours |
Total fee | ₹1,599 |
Mode of learning | Online |
Difficulty level | Intermediate |
Credential | Certificate |
Python for Data Science Essential Training Part 1 at Linkedin Learning Highlights
- Earn a sharable certificate
- 1 exercise file
- 7 quizzes
- Access on tablet and phone
Python for Data Science Essential Training Part 1 at Linkedin Learning Course details
- Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning
- It has now been updated and expanded to two parts—for even more hands-on experience with Python
- In this course, instructor Lillian Pierson takes learner step by step through a practical data science project: a web scraper that downloads and analyzes data from the web
- Learner should walk away from this training with basic coding experience that learner can take to organization and quickly apply to own custom data science projects
Python for Data Science Essential Training Part 1 at Linkedin Learning Curriculum
Introduction
Data science life hacks
What you should know
Introduction to the Data Professions
Introduction to the data professions
The four flavors of data analysis
Why use Python for analytics?
High-level course road map
Data Preparation Basics
Filtering and selecting
Treating missing values
Removing duplicates
Concatenating and transforming
Grouping and aggregation
Data Visualization 101
The three types of data visualization
Selecting optimal data graphics
Communicating with color and context
Practical Data Visualization
Creating standard data graphics
Defining elements of a plot
Plot formatting
Creating labels and annotations
Visualizing time series
Creating statistical data graphics
Basic Math and Statistics
Simple arithmetic
Basic linear algebra
Generating summary statistics
Summarizing categorical data
Parametric correlation analysis
Non-parametric correlation analysis
Transforming dataset distributions
Extreme value analysis for outliers
Multivariate analysis for outliers
Data Sourcing via Web Scraping
BeautifulSoup object
NavigableString objects
Data parsing
Web scraping in practice
Introduction to NLP
Cleaning and stemming textual data
Lemmatizing and analyzing textual data
Collaborative Analytics with Plotly
Introduction to Plotly
Create statistical charts
Line charts in Plotly
Bar charts and pie charts in Plotly
Create statistical charts
Conclusion
Next steps
Other courses offered by Linkedin Learning
Python for Data Science Essential Training Part 1 at Linkedin Learning Students Ratings & Reviews
1 Rating- 3-41
Student Forum
Anything you would want to ask experts?
Data ScienceData Science BasicsPython for data sciencePython for Data Science Essential Training Part 1