Foundational Python for Data Science
Python language has been around for a long time and has worn many hats. Its applications include everything from web development, to film, government, science, and business. You can gain a hands-on experience in Python for Data Science with uCertify’s course Foundational Python for Data Science. This course will not teach the Python needed to set up a web page or perform system administration. It is also not intended to teach you Data Science, but rather the Python needed to learn Data Science. It has well-descriptive interactive lessons containing knowledge checks, quizzes, flashcards, and glossary terms to get a detailed understanding of Python needed to learn Data Science.
- Price: $279.99
- Delivery Method: eLearning
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Test Prep
36+ Pre Assessment Questions |
2+ Full Length Tests |
37+ Post Assessment Questions |
74+ Practice Test Questions
Features
Why choose TOPTALENT?
- Get assistance every step of the way from our Texas-based team, ensuring your training experience is hassle-free and aligned with your goals.
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- Have confidence in an exceptional 95% approval rating from our students, reflecting outstanding satisfaction with our course content, program support, and overall customer service.
- Benefit from being taught by Professionally Certified Instructors with expertise in their fields and a strong commitment to making sure you learn and succeed.
Outline
Lessons 1:
Introduction
- About This eBook
Lessons 2:
Introduction to Notebooks
- Running Python Statements
- Jupyter Notebooks
- Google Colab
- Summary
- Questions
Lessons 3:
Fundamentals of Python
- Basic Types in Python
- Performing Basic Math Operations
- Using Classes and Objects with Dot Notation
- Summary
- Questions
Lessons 4:
Sequences
- Shared Operations
- Lists and Tuples
- Strings
- Ranges
- Summary
- Questions
Lessons 5:
Other Data Structures
- Dictionaries
- Sets
- Frozensets
- Summary
- Questions
Lessons 6:
Execution Control
- Compound Statements
- if Statements
- while Loops
- for Loops
- break and continue Statements
- Summary
- Questions
Lessons 7:
Functions
- Defining Functions
- Scope in Functions
- Decorators
- Anonymous Functions
- Summary
- Questions
Lessons 8:
NumPy
- Installing and Importing NumPy
- Creating Arrays
- Indexing and Slicing
- Element-by-Element Operations
- Filtering Values
- Views Versus Copies
- Some Array Methods
- Broadcasting
- NumPy Math
- Summary
- Questions
Lessons 9:
SciPy
- SciPy Overview
- The scipy.misc Submodule
- The scipy.special Submodule
- The scipy.stats Submodule
- Summary
- Questions
Lessons 10:
Pandas
- About DataFrames
- Creating DataFrames
- Interacting with DataFrame Data
- Manipulating DataFrames
- Manipulating Data
- Interactive Display
- Summary
- Questions
Lessons 11:
Visualization Libraries
- matplotlib
- Seaborn
- Plotly
- Bokeh
- Other Visualization Libraries
- Summary
- Questions
Lessons 12:
Machine Learning Libraries
- Popular Machine Learning Libraries
- How Machine Learning Works
- Learning More About Scikit-learn
- Summary
- Questions
Lessons 13:
Natural Language Toolkit
- NLTK Sample Texts
- Frequency Distributions
- Text Objects
- Classifying Text
- Summary
- Questions
Lessons 14:
Functional Programming
- Introduction to Functional Programming
- List Comprehensions
- Generators
- Summary
- Questions
Lessons 15:
Object-Oriented Programming
- Grouping State and Function
- Special Methods
- Inheritance
- Summary
- Questions
Lessons 16:
Other Topics
- Sorting
- Reading and Writing Files
- datetime Objects
- Regular Expressions
- Summary
- Questions
