Key Information
Python Developer Certificate
Data Science Certificate
Python for Data Science Bootcamp
$4995 138 Hours
$3495 84 Hours
$1495 30 Hours
Overview
Learn the essential skills and tools to become a Python Developer. This beginner-friendly course teaches students Python for software development with Django and Django REST in addition to other developer tools such as Git and SQL. 
Master the tools to become a data scientist: Python, SQL, automation, and machine learning. Learn Python programming fundamentals and analyze data with Pandas, NumPy, and Matplotlib, and query databases with SQL. Use machine learning to apply regressions and other statistical analysis to create predictive models.
Pick up Python fundamentals and quickly transition into analyzing real-world datasets. You will learn to how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions.
Prerequisite
Open to Beginners
Open to Beginners
Open to Beginners
Location
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
Scheduling Options
Weekdays or weeknights
Weekdays, weeknights, or weekends
Weekdays, weeknights, or weekends
Next Start Date
February 22–March 24, Monday to Friday, 10–5pm
Jan 19–Feb 8, Weekdays
January 25–29, Monday to Friday, 10–5pm
Certification
Receive a Certificate of Completion
New York-licensed Certificate Program
Receive a Certificate of Completion
Free Retake Within 1 Year See our class policies for more details
Workbook Included
Courses Included (Certificates only)
N/A
  • 30 HoursPython for Data Science Bootcamp
  • 30 HoursPython Machine Learning Bootcamp
  • 18 HoursSQL Bootcamp
  • 6 HoursPython for Automation
N/A
Discounts See our discounts policies for more details
  • This program is a 60+ hour bootcamp, already priced at a discounted rate. Other discounts do not apply.
  • This is a discounted package of classes that is 15–25% off the individual class prices. Other discounts do not apply.
  • Shorter courses such as this are already affordably priced and are not eligible for discounts.
Payment Plan See our payment plan FAQ for more details
This program is eligible for our “pay-as-you-go” payment plan.
This program is eligible for our “pay-as-you-go” payment plan.
Target Audience
Anyone
  • Individuals looking to break into data science with Python, machine learning, and SQL skills
  • Analysts who work with other data tools looking to transition to Python and SQL
  • Developers looking to broaden their skillset to data science and Python
  • Individuals looking to break into the field of data science with Python
  • People with minimal coding background who want to move into more data-centric work at their current workplace
  • People who work with data in tools like SPSS, STATA, or MATLAB and would like to transition into using Python and SQL.
  • Developers with experience in other arenas, who would like to work in data science
What You’ll Learn
  • Fundamentals of Python and Object-Oriented Programming
  • Deploy Projects to Github using Git 
  • Automate Tasks using Python and Django 
  • Interact with APIs using REST
  • Build a portfolio of projects throughout the course
  • Analyze tabular data with NumPy and Pandas
  • Create graphs and visualizations with Matplotlib
  • Make predictions with linear regression 
  • Applying Machine learning algorithms to the data
  • Cleaning and balancing data in Pandas
  • Evaluating the performance of machine learning models  
  • Combine information across tables with join statements
  • Advanced techniques such as subqueries and stored procedures 
  • Learn how to write programs in Python to automate everyday tasks 
  • Foundational programming concepts including loops, functions, and objects
  • Handle different types of data, such as integers, floats, and strings
  • Control the flow of your programs with conditional statements
  • Reuse and simplify code with object-oriented programming
  • Analyze tabular data with Numpy and Pandas
  • Create graphs and visualizations with Matplotlib
  • Make predictions with linear regression, using scikit-learn