# Python Data Science & Machine Learning Program NYC (High School & College)

Canonical URL: <https://www.nobledesktop.com/classes/python-data-science-summer-camp-nyc>

## Overview

Python is one of the leading programming languages used by developers today. It is the ideal language for beginners because it is both powerful and beginner-friendly.

In the first half of this hands-on Python course, you will begin by learning Python fundamentals and then move on to more advanced programming tasks. The second half of the course focuses primarily on data science using Pandas, Matplotlib, and scikit-learn. These libraries will help you input, analyze, and visualize data.

This course will be held in person in NYC over two weeks during the summer (10 a.m.–4 p.m. each day, with a one-hour lunch break). The Python summer course is also available live online.

**Prerequisites and Ages:** The program is ideal for high school students with a strong interest in coding. No prior coding experience is required, but students should be comfortable with basic computer use. This course is great for any teen interested in coding, finance, journalism, marketing, or communication.

## What you'll learn

- Programming fundamentals in Python
- How to write conditional statements in Python
- Import and manipulate data using the Pandas library
- Clean, transform, and wrangle data
- Visualize and interpret complex data using Matplotlib
- Apply machine learning algorithms with scikit-learn

## Curriculum

#### Introduction to Programming

- History of Python
- Understanding Hardware
- Anaconda Distribution
- Jupyter Notebook Fundementals
- Writing First Program (“Hello World”)

#### Terminal Commands

- Navigate & Manipulate Directory Strcutres
- Edit Files
- Basic Scripting

#### Python Fundamentals

- Data Types
- Operators
- Expression
- Indexing & Slicing
- Strings
- Conditionals
- Functions
- Control Flow
- Nested Loops
- Sets & Dictionaries

#### Data Science Fundementals

- Import Data
- Functions
- Basic Data Tool

#### Advanced Python Fundementals

- Lists
- Mutating Operations
- Tuples, Sets, Dictionaries
- Loops
- Control Flow
- List Comprehension
- Error Handeling

#### Processing

- String Methods
- Read & Write to Text Files
- Natrual Language Processing
- Mini Project

#### Object Oriented Programming

- Classes
- Constrcutors
- Object Methods
- Writing Modules
- Advanced Scripting
- Terminal & Socket Connection

#### Numerical Python

- Arrays
- Universal Functions
- Concatenating, Indexing, Slicing
- Arithmetic & Boolean Operations

#### Python Data Analysis:Pandas 1

- Data Series
- Data Frames
- Import CSV & Excel Files
- Organize Data Frames
- Data Manipulation
- Descriptive Statstics

#### 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

### Machine Learning Fundamentals

#### 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

## Schedule
- Jun 29, 2026 – Jul 17, 2026 — NYC
- Jun 29, 2026 – Jul 17, 2026 — NYC
- Jul 20, 2026 – Jul 30, 2026 — NYC
- Aug 3, 2026 – Aug 13, 2026 — NYC

## Pricing

**Tuition:** $2195