Python Bootcamps Chicago: Immersive Python Training Programs

Key Information	Python Machine Learning Immersive	Python for Data Science Immersive	Data Science Certificate
	$1,895 30 Hours	$1,495 30 Hours	$3,495
	Learn More	Learn More	Learn More
	Download Syllabus	Download Syllabus	Download Syllabus

Overview	Take a step beyond normal programming, into using algorithms that can independently learn patterns and make decisions. Machine learning skills are in high demand, as these algorithms now run the majority of trading on Wall Street and the product recommendations at big companies like Amazon, Spotify, and Netflix.	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.	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.
Prerequisite	This course does require students to be comfortable with Python and its data science libraries (NumPy and Pandas). If a student has not worked in Python before, we require a student to enroll in our Python for Data Science Immersive before taking this course.	Open to Beginners	Open to Beginners
Location	29 E Madison, Chicago or Live Online	29 E Madison, Chicago or Live Online	29 E Madison, Chicago or Live Online
Schedule	Not currently scheduled	Not currently scheduled	Not currently scheduled
Certification	Receive a Certificate of Completion	Receive a Certificate of Completion	New York-licensed Certificate Program
Free Retake Within 1 Year See our class policies for more details
Workbook Included
Courses Included (Certificates & packages only)	N/A	N/A	30 HoursPython for Data Science Immersive 30 HoursPython Machine Learning Immersive 6 HoursPython for Automation 18 HoursSQL Bootcamp
Discounts See our discounts policies for more details	Shorter courses such as this are already affordably priced and are not eligible for discounts.	Shorter courses such as this are already affordably priced and are not eligible for discounts.	This is a discounted package of classes that is 15–25% off the individual class prices. Other discounts do not apply.
Payment Plan See our payment plan FAQ for more details			This program is eligible for our “pay-as-you-go” payment plan.
Financing See our Leif FAQ for more details
Target Audience	Confident python developers who would like to explore machine learning hands-on Developers with strong skills in another language, and some background working with data looking to building machine learning models	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
What You’ll Learn	How to clean and balance your data using the Pandas library Applying machine learning algorithms such as logistic regression and random forest using the scikit-learn library Choosing good features to use as input for your algorithms Properly splitting data into training, test and cross-validation sets Important theoretical concepts like overfitting, variance and bias Evaluating the performance of your machine learning models	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	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

Earn a Data Science Certificate