Key Information	Python for Data Science Bootcamp	Python Machine Learning Bootcamp	SQL Bootcamp
	$1,495 30 Hours	$1,895 30 Hours	$975 18 Hours
	Learn More	Learn More	Learn More
	Download Syllabus	Download Syllabus	Download Syllabus

Overview	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.	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.	Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL
Prerequisite	Open to Beginners	This course requires 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 Bootcamp before taking this course.	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
Schedule	Next start date: April 3–May 10, Mondays & Wednesdays, 6–9pm, except Apr 5, Apr 19 Other scheduling options Weeknights, weekdays, or weekends View full schedule	Next start date: July 3–August 2, Mondays & Wednesdays, 6–9pm Other scheduling options Weeknights, weekdays, or weekends View full schedule	Next start date: April 3–24, Mondays & Wednesdays, 6–9pm, except Apr 5 Other scheduling options Weeknights, weekends, or weekdays View full schedule
Certification	Receive a Certificate of Completion	Receive a Certificate of Completion	Receive a Certificate of Completion
Free Retake Within 1 Year See our class policies for more details
Workbook Included
Payment Plan See our payment plan FAQ for more details
Financing See our Leif FAQ for more details
Target Audience	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	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	Leaders interested in making better data-driven decisions and “knowing the numbers” Analysts looking to deepen their skillset beyond Excel and Tableau Developers who want to be more comfortable working with databases
What You’ll Learn	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	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	Explore information stored in a database (tables, columns, rows, etc.) using the graphical interface of DBeaver (a popular free database app) Write SQL queries to retrieve data from tables in a database Combine information from multiple tables with JOIN statements Filter data, group it, and sort it to extract the specific info you need Advanced techniques like Subqueries, String Functions, and IF‑Else logic with CASE How to use Views and Functions with parameters instead of directly querying tables

Enroll in an Upcoming Data Science Course

March 2023
Python Machine Learning Bootcamp March 28–April 4 Tuesday to Monday 10–5pm EDT	$1,895 30 Hours	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.
April 2023
Python for Data Science Bootcamp April 3–May 10 Mondays & Wednesdays 6–9pm EDT	$1,495 30 Hours	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.
SQL Bootcamp April 3–24 Mondays & Wednesdays 6–9pm EDT	$975 18 Hours	Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL
SQL Bootcamp April 15–29 Saturdays 10–5pm EDT	$975 18 Hours	Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL
June 2023
Python for Data Science Bootcamp June 12–16 Monday to Friday 10–5pm EDT	$1,495 30 Hours	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.
SQL Bootcamp June 20–22 Tuesday to Thursday 10–5pm EDT	$975 18 Hours	Learn to extract info from databases by writing SQL queries, joining tables, aggregating data, and filtering results. You’ll learn PostgreSQL in this class, but the concepts apply equally to other databases such as SQL Server and MySQL
July 2023
Python Machine Learning Bootcamp July 3–August 2 Mondays & Wednesdays 6–9pm EDT	$1,895 30 Hours	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.
Python Machine Learning Bootcamp July 5–11 Wednesday to Tuesday 10–5pm EDT	$1,895 30 Hours	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.
Python Machine Learning Bootcamp July 8–August 5 Saturdays 10–5pm EDT	$1,895 30 Hours	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.
Python for Data Science Bootcamp July 17–21 Monday to Friday 10–5pm EDT	$1,495 30 Hours	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.

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Enroll in an Upcoming Data Science Course