Python Data Science & Machine Learning Live Online (High School & College)
- Format
- Live or Self-paced
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Book live on Noble DesktopSummary
This course will cover the fundamentals of Python programming and its applications in data science and machine learning. Students will get up and running in Python quickly and be ready to use Python for data analysis projects.
Python is one of the leading languages used by programmers today. It is the ideal language for beginners because it's both powerful and easy to learn.
In the first half of this hands-on Python course, you will begin by learning the fundamentals of Python code and then transition into more complicated programming tasks. The second half of the course focuses primarily on data science using Pandas, Matplotlib, and scikit-learn. These packages will teach you how to input, analyze, and visualize data.
Class Notes
- Method of Delivery: Live Online (live-streamed with the ability to ask questions and interact with the instructor in real-time).
- Prerequisites & Ages: The program is ideal for high school and college students with a strong interest in coding. Prior coding/programming experience is not required, but students must be comfortable with computer basics.
- Computer: Live online attendees should have their own Mac or PC. We will assist with any software setup prior to the course.
Curriculum
What you'll learn
- Programming fundamentals in Python
- How to write conditional statements in Python
- Import and manipulate data using the Pandas package
- Clean and wrangle data
- Visualize and interpret complex data
- Use machine learning algorithms
Course syllabus
Day 1-3
Introduction to Programming
- History of Python
- Understanding Hardware
- Anaconda Distribution
- Jupyter Notebook Fundamentals
- Writing First Program (“Hello World”)
Terminal Commands
- Navigate & Manipulate Directory Structures
- Edit Files
- Basic Scripting
Python Fundamentals
- Data Types
- Operators
- Expression
- Indexing & Slicing
- Strings
- Conditionals
- Functions
- Control Flow
- Nested Loops
- Sets & Dictionaries
Data Science Fundamentals
- Import Data
- Functions
- Basic Data Tool
Advanced Python Fundamentals
- Lists
- Mutating Operations
- Tuples, Sets, Dictionaries
- Loops
- Control Flow
- List Comprehension
- Error Handling
Day 4-5
Processing
- String Methods
- Read & Write to Text Files
- Natural Language Processing
- Mini Project
Object Oriented Programming
- Classes
- Constructors
- Object Methods
- Writing Modules
- Advanced Scripting
- Terminal & Socket Connection
Day 6-8
Numerical Python
- Arrays
- Universal Functions
- Concatenating, Indexing, Slicing
- Arithmetic & Boolean Operations
Day 9-10
Python Data Analysis: Pandas 1
- Data Series
- Data Frames
- Import CSV & Excel Files
- Organize Data Frames
- Data Manipulation
- Descriptive Statistics
Advanced Python
- File Input
- User Input
- List Comprehension
- Packages
Data Analysis
- Cleaning Data
- Filtering Data
- Advanced Grouping
- Pivot Tables
Data Visualization
- Plotting with Matplotlib
- Scatter Plots
- Histograms & Bar Plots
- Custom Visualizations
Day 11-15
Basic Regression Analysis
- Linear Regression
- Mean squared error
- Training set vs Test set
- Cross validation
Advanced Regression Analysis
- Multi-linear regression
- Feature engineering
- Overfitting
Classification
Logistic Regression
- Regression vs Classification
- Logistic Regression
- Sigmoid function
K-nearest Neighbors
- K-nearest neighbors
- Model-based vs memory-based
- Parametric vs non-parametric
- Evaluating performance
Final Project
Details
- Curate Data
- Import, Clean, and Merge Data
- Analyze Data
- Visualize Data
- Present Results
What's included
- Course workbook
- Class recordings
Stated by the provider. Confirm what your tuition covers before enrolling.
Live classes
Choose dates and book your instructor-led class on nobledesktop.com.
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Live online
Starts at 10:00 · America/New_York (EDT); final session ends at 13:00 EDT
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Live online
Starts at 13:30 · America/New_York (EDT); final session ends at 16:30 EDT
-
–
Live online
Starts at 10:00 · America/New_York (EDT); final session ends at 16:00 EDT
-
–
Live online
Starts at 10:00 · America/New_York (EDT); final session ends at 16:00 EDT
Confirm current dates and availability on Noble Desktop before booking.
Self-paced course
Learn through recorded lessons on your own schedule.
This course is available for 30 days. You can choose when to start your access period. Once you activate, you will have 30 days to complete it (access the course materials, quizzes, projects and videos). You may request one extension of seven (7) days. Other extension requests will be evaluated on a case-by-case basis. Videos are not downloadable.
- Tuition
- $1,699
- Course length
- 45 hours
- Schedule
- On your schedule
This course covers the fundamentals of Python programming and its applications in data science and machine learning. Students will quickly get up and running with Python and learn how to use it for data analysis projects. Python is one of the leading programming languages used today. It is an ideal language for beginners because it is both powerful and approachable.
In the first half of this hands-on course, students learn the fundamentals of Python code before moving into more advanced programming tasks. The second half focuses on data science using Pandas, Matplotlib, and scikit-learn. Through these tools, students learn how to input, analyze, and visualize data.
This program is ideal for high school students with a strong interest in coding. Prior coding or programming experience is not required, but students should be comfortable with basic computer skills.
Self-paced curriculum
What you'll learn self-paced
- Master Python fundamentals like data types, conditionals, loops, and functions.
- Clean and manipulate real-world data using Pandas and NumPy.
- Process files, utilize string methods, and handle structured data.
- Create custom charts, histograms, and plots with Matplotlib.
- Apply machine learning techniques such as linear regression, classification, and K-nearest neighbors.
- Complete a capstone project to showcase your ability to analyze and present data insights.