Data Science Classes NYC

In this comprehensive data science program, individuals will learn a variety of critical skills to become a data scientist. Students will learn to code with Python, create machine learning models, automate tasks like web scraping, and interact with databases using SQL. Topics include data analysis with Python's Numpy and Pandas packages, data visualization, predictive analytics, machine learning, SQL querying, Python automation, and web scraping. Students will learn hands-on by working in Python and SQL and will complete the program with the skills they need to enter the field of data science. This program offers flexible scheduling and provides a free retake for students to refresh the material.

In this course, students expand their Python programming skills into machine learning and algorithms that can independently learn patterns and make decisions. The course begins with linear and logistic regressions, the most time-tested and reliable tools for approaching a machine learning problem. Students then progress to algorithms with a different theoretical basis, such as k-nearest neighbors, decision trees, and random forest. This will bring important statistical concepts to the forefront, such as bias, variance, and overfitting. Participants also learn how to measure the accuracy of your models, as well as tips for choosing effective features and algorithms.

In this data science bootcamp, students will build programming skills and data analysis skills using Python. This course is open to beginners and is meant to get individuals up and running with Python programming and data science to generate insights from data. Topics covered include programming fundamentals, working with data frames, data analysis, data visualization, and statistical analysis. This course offers flexible scheduling options and a free retake for students to refresh the materials.

The Data Science Bootcamp from Flatiron is designed to be a comprehensive data science program for students to start careers in data science. The program runs for 15-weeks and covers the key components for data science, including SQL, Python, statistics, and machine learning. Students will start coding in Python using Jupyter notebooks, learn the statistics behind machine learning, apply machine learning techniques, and work on data science projects in this data science course. In addition to the coursework, students will receive career coaching and job support during the program.

In this Python automation course, students will learn to automate tasks using Python for various applications. This course is meant for those with prior Python experience looking to learn automation techniques like scheduling programs, updating spreadsheets, and web scraping. Topics include HTML and CSS basics, web scraping techniques, working with spreadsheets using Python, and scheduling scripts. This course offers flexible scheduling options plus a free retake for students to refresh the material.

Learn to problem solve, and effectively communicate, like an analyst. This course teaches you to use industry-standard tools to make ethical, data-driven decisions. Experience hands-on training to master SQL, Excel, Tableau, PowerBI, and Python – tools listed in virtually every data analytics job posting across industries.

This 35-hour program offers a comprehensive introduction to R. This course teaches the skills needed to process, manipulate, and analyze data, create visualizations, and generate reports. The program begins with an overview of programming with R. It then moves on to the treatment of basic data elements, the use of “dplyr” to manipulate data, and how to create basic and advanced visualizations such as violin and mosaic plots, and time-series diagrams.

This six-week course teaches students how to use key components of Apache Hadoop, Spark, MapReduce, and more. Using platforms such as Databricks, Amazon Web Services, and Docker, students will learn how to use Python and cloud computing to run exercises. Students will complete five units on topics such as Hadoop, MapReduce, Apache Hive, Apache Pig, Apache Spark, and Amazon Web Services.

This data science with Python course is for people with a basic knowledge of programming with Python. This comprehensive course will explain how to work with some of the most widely-used data analysis and visualization modules, such as Pandas, matplotlib, Numpy, Scipy, and more. The course will begin with a review of the basic syntax and data structures of Python before moving on to object-oriented programming, scientific computation, and data visualization. The final unit will teach you how to manipulate data with Pandas before you complete a final project.

Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling. 

This 1-week data analytics course provides a deep-dive into using Python for data analysis. Students will get comfortable with the basics of Python programming and start working with critical data analysis libraries like Numpy, Pandas, and Matplotlib to perform data analysis and create data visualizations. This 35 hour intensive is meant to quickly get beginners in Python up to speed on performing data analysis and visualization in Python.

This comprehensive Python course teaches beginners how to code, analyze data, and create machine learning models with Python. Students will start with the basics of programming in Python and build up their data skills on their way to learning machine learning and automation. Topics include programming fundamentals, data analysis, data visualization, machine learning, automation, and web scraping. This course offers flexible scheduling options and provides a free retake so students can refresh the material.

In this 3-day bootcamp, beginners will be transformed into confident SQL users who can write queries, manipulate tables, and store advanced code. Participants will start by learning about relational databases and SQL fundamentals and will conclude the program having mastered complex retrieval tasks and storing complex code. Topics include composing queries, creating your SQL databases, automating workflow with stored procedures, and step-by-step exercises that will provide an efficient and thorough approach to mastering SQL. Tuition includes hands-on training, a free retake, and a course manual. The course has flexible scheduling options and is available online and in NYC.

In this 18-hour SQL Bootcamp open to beginners, participants will discover the essentials of databases and how to write SQL code to retrieve and analyze data. Through hands-on exercises, participants learn everything from data types to basic queries and advanced topics, including aggregating and joining. Topics include SQL GUI basics, fundamental to advanced querying, table creation, joins, views, functions, and external data connections. The course is taught using PostgreSQL and applies to other relational databases, including SQL Server and MySQL. Participants can retake the course for free within one year.

This data science program uses project-based learning to teach students data analysis, modeling, and programming in Python. Using Synapse, a data-driven Learning Management System, students will learn how to clean and analyze data, create visualizations, and use the fundamental components of programming to work with Python, Pandas, and NumPy. Students can take advantage of online and on-campus options.

Create robust predictive models with statistics and Python programming. Build confidence and credibility to tackle complex machine learning problems on the job. This course is offered in person and live online, in a remote classroom setting.

This data science bootcamp is an immersive program intended to give you the real-world skills needed to become a data scientist. This program teaches skills in Python and R, combining those tools with principles of machine learning, data visualization, and analytics. You will learn how to build statistical models and linear regressions using tools such as Hadoop, Spark, AWS, and much more. Upon completion of this 12-week program, students will be ready to begin a career in data science.

This immersive course prepares students to become Data Scientists with lessons in Python, machine learning, automation, and SQL. The courses are hands-on with multiple projects throughout that students can add to their portfolios.

This course in machine learning with R introduces novice R programmers a foundation in machine learning theory. The course covers the foundations of statistics and simple linear regressions, multiple linear regression and generalized linear models, kNN and Naïve Bayes, the curse of dimensionality, tree models, and SVMs. Students who complete this course will understand the mathematics behind machine learning algorithms and be able to use them in real-world situations.

This Python machine learning course teaches machine learning methods and modules with the Python code designed to implement them. The units of this course explain simple and complex linear regressions, classification methods for logistic regression, discriminant analysis, and naïve Bayes, support vector machines and tree-based methods, regularization strategies, and how to use clustering algorithms. Completion of this 20-week course will prepare students to use machine learning algorithms to analyze complex datasets and make logical predictions.