Python Bootcamp NYC
IDCML

Python bootcamp classes in-person in NYC (34th & Madison Ave), onsite, or online from anywhere

Study Python to master data analysis, machine learning, and automation. Build predictive models, design interactive dashboards, and bring data to life through visualization. Get the skills you need for a career in data science with tools like Python, NumPy, Pandas, and Matplotlib.

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This program includes

  • 96 hours of live, project-based training from experts
  • Software Access
  • Additional elective course
  • Additional 1-on-1 mentoring outside of class
  • Retake for free within 1 year
  • Access to class recordings (30 days)
  • Verified digital certificate of completion
  • Learn at an accredited institution

Special Promotion: Choose one free elective (Python for AI or Machine Learning Advanced) when you register for this certificate program. Contact us after enrolling to be added to the class.

In this program, you’ll learn how to use Python for data science, machine learning, visualization, and automation. Starting with the fundamentals, you’ll develop the programming skills to work with databases and perform meaningful data analysis. By the end, you’ll be ready to apply for entry-level roles in data science and Python engineering.

As you progress, you’ll work with core libraries like NumPy, Pandas, and Matplotlib to analyze data and build predictive models with scikit-learn. You’ll also explore how Python can automate everyday tasks, such as collecting, cleaning, and formatting data. In the final stage, you’ll create interactive dashboards and visualizations with tools like Seaborn, Plotly, and Dash, and publish them to GitHub so potential employers can see your work in action.

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Add additional skills with a certificate program:

Courses in this Certificate Program

This is the recommended order, but some courses may be taken in a different order.

Download Syllabus PDF

Unit 1 30 Hours

Python for Data Science Bootcamp
  • Learn Python fundamentals, including variables, data types, functions, loops, and control flow, for building robust programs
  • Work with complex data structures such as dictionaries and lists to efficiently organize and access data
  • Use NumPy and Pandas to import, clean, and manipulate datasets for analysis and exploration
  • Generate descriptive statistics and apply filtering, grouping, and pivoting techniques to gain deeper insights
  • Visualize data using Matplotlib and create clear, customized charts, including bar graphs, histograms, and scatter plots
  • Gain the practical skills needed to transition into machine learning with a solid understanding of data science workflows

Unit 2 30 Hours

Python Machine Learning Bootcamp
  • Explore foundational techniques like linear and logistic regression for modeling numerical and categorical data
  • Understand the difference between regression and classification problems and when to apply each approach
  • Build and evaluate models using k-nearest neighbors, decision trees, and ensemble methods like random forest
  • Learn key concepts such as cross-validation, training vs. test sets, and performance metrics like mean squared error
  • Apply feature engineering techniques to improve model accuracy while managing overfitting and bias-variance tradeoffs
  • Use Python's essential data science libraries, NumPy, Pandas, and scikit-learn, to structure data and implement algorithms
  • Gain insights into how machine learning powers systems at companies like Netflix, Spotify, and Amazon
  • Complete a final portfolio project that demonstrates your ability to apply machine learning to solve real problems

Unit 3 6 Hours

Python Automation Course
  • Understand how websites are structured with HTML and CSS to identify elements for data extraction
  • Learn Python fundamentals, such as variables, data types, conditionals, loops, and list manipulation
  • Use the Requests and Beautiful Soup libraries to perform web scraping and target specific content
  • Write loops to automate web scraping across multiple pages and streamline repetitive tasks
  • Store scraped data in different formats, such as text files and CSVs, for analysis and reporting
  • Schedule Python scripts to run on a regular basis, enabling continuous data collection and automating workflows

Unit 4 24 Hours

Python Data Visualization & Interactive Dashboards

Transform raw data into interactive visual insights by building dashboards with Python’s top visualization tools. This course blends analysis, design, and deployment to help you showcase data professionally.

  • Work with real-life datasets using Python’s core libraries, including NumPy for numerical computing and Pandas for data manipulation
  • Create static and interactive visualizations using Matplotlib, Seaborn, and Plotly to clearly communicate trends and patterns
  • Build multi-component dashboards using Dash Enterprise, incorporating callbacks, sliders, date pickers, and more
  • Practice hands-on development by applying new skills to personalized projects with guided instructor support
  • Publish your dashboards online using GitHub and Heroku to demonstrate your work to potential employers or clients
  • Explore best practices for styling and structuring visual narratives that are clear, persuasive, and engaging

Choose between Python for AI & Machine Learning Advanced for free as part of this certificate. Choose your date after you register for the program. 

Bonus 30 Hours

Python for AI: Create AI Apps with Flask & OpenAI

Learn how to build AI-powered web applications using Flask and the OpenAI API. This course covers web development fundamentals, API integration, and AI-driven features for interactive applications.

  • Set up Flask projects and create routes for handling web requests and rendering templates.
  • Design and style web applications using HTML, CSS, and Flask’s templating system.
  • Integrate the OpenAI API to implement AI-powered features like sentiment analysis.
  • Handle user input with dynamic forms and process data for real-time interactions.
  • Implement error handling and debugging techniques to ensure smooth application performance.
  • Deploy and test Flask applications for real-world use and AI-enhanced functionality.

Bonus 30 Hours

Python Machine Learning Advanced

Gain hands-on experience with advanced machine learning techniques as you build and deploy real-world projects across natural language processing, recommendation systems, forecasting, deep learning, and computer vision.

  • Build and deploy full-stack applications with Flask
  • Implement collaborative and content-based recommendation engines
  • Forecast trends using advanced time series modeling with Facebook Prophet
  • Train and evaluate convolutional neural networks using PyTorch
  • Perform real-time object detection in images and video streams with YOLO
  • Apply NLP techniques to build effective sentiment analysis models

Schedule & Enrollment: Python Bootcamp NYC

  • 96 Hours
  • Price before discounts: $5,510 Full tuition: $3,495
  • NYC or Live Online
  • Free retake
  • Payment plans
  • Software Access
  • 1:1 Mentoring included

  • Custom Schedule
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  • Oct 27–Nov 14 Show package courses
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  • Dec 1–19 Show package courses
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  • Dec 14–Mar 29 Show package courses
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  • Jan 5–Apr 20 Show package courses
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  • Jan 26–Feb 13 Show package courses
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  • Apr 21–Jul 30 Show package courses
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