Data Science Classes Worcester, MA

This data science program is designed to help individuals with a math background and some familiarity with Python programming bolster their skills and get up to speed and launch their data career. Through their blended learning model, students will be able to hone their data skills through fundamental preparatory work, in-class project work, and though the support of a devoted career coach. Students in this course will start their data science journeys by learning fundamental concepts around Python programming and leveraging programming tools like GitHub. As the course progresses, students will explore additional programming concepts like NumPy, utilizing Unix commands, using Pandas to clean and extract data, and web scraping tools. The course also covers statistical modeling and regressions, machine learning models, NLP, and a few other advanced topics and trends that are helpful to data scientists of all levels.

This data science course is a 10-week, part-time program for individuals with backgrounds in programming or a quantitative field. Utilizing a hands-on approach, students learn by doing to build vibrant skills that are essential in any field that leverages big data. The course curriculum centers around Python programming and data exploration, data modeling, and machine learning. Graduates of the Data Science course will be able to showcase their strong understanding of Python programming and applied statistics through their capstone projects, which are also a great springboard to a career in data science.

This course introduces young programmers to topics in data science, including data visualization, machine learning, artificial intelligence, and natural language processing. Students work with Python tools, SQL, Matplotlib, and scikit-learn as they make data analyses and build machine learning models.

In this part-time bootcamp, students learn necessary programming skills to manipulate databases and perform various levels of analysis on the data. This program prepares students for entry-level data science and Python engineering positions.

This data analytics course is a 40-hour in-person or online program for individuals with no prior experience with data analytics. Utilizing a hands-on approach, students learn by doing in order to build vital and dynamic skills that are applicable in a wide range of industries. The course curriculum centers around the core processes all data analysts must know, including data collection, cleaning, analyzing, and data visualization best practices. Students also come away with hands-on experience using some of the most common tools in the industry, including Microsoft Excel, SQL, and Tableau. By the end of the course, students will have a better understanding of how to gain insights from data and feel more prepared for a possible career in data analytics.

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 course teaches basic SQL Querying in 2-days. Students learn online, attending live training provided by professional instructors. The course explores database concepts such as grouping and summarizing data, joining tables, and clauses. Working in the online lab environment, students will get hands-on experience writing simple SELECT queries and using built-in functions and expressions.

This 1-day online course teaches students how to compose Advanced queries in SQL. Based on Microsoft’s SQL Server, this program is delivered live by experienced instructors, allowing for real-time feedback. Students will learn how to write advanced queries, advanced WHERE clauses, and create advanced joining tables. They will practice these schools in an online lab environment, where they can collaborate with other students.

This course is a 4-day comprehensive workshop on MySQL workbench data modeling and development. This program uses an online lab environment to allow students to practice what they are learning. The live training covers topics such as creating an ERD, defining the physical schemata, reverse engineering a database, managing security, and more. Students will also learn how to use MySQL Workbench to create and maintain MySQL databases effectively.

This machine learning course is meant for learners looking to master the concepts needed for machine learning. Students will learn how machine learning can be used for decision-making, the different machine learning techniques available, and how to tackle machine learning projects. The course covers various techniques in machine learning, including regression, classification, k-means, neural networks, and more.