Data Classes London

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.

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.

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 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 covers the skills needed to become a Data Analyst or Business Analyst, including data analytics fundamentals, visualization with Tableau, using Python to clean and manipulate data, and how to work with relational databases. One-on-one mentoring is included.

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.

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.

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.

This 1-day course gives a foundational understanding of Microsoft Excel. Students with novice computer skills will learn how to manipulate and organize data using Excel spreadsheets. They will also learn how to navigate the Excel interface, create, manage and save workbooks, and perform calculations. This program is available both face-to-face and with live online instruction.

In this 1-day course, students will learn how to use some of the more advanced features of Microsoft Excel. With online and in-person options, students will learn how to work with functions, lists, tables, conditional formatting, charts, and PivotTables. After completing this course, students will be able to leverage Excel’s capabilities to analyze and present data.