Data Analytics Flex Self Paced
24 Weeks · Online · Live 1:1 Mentorship · Fast Support
24 Weeks · Online · Live 1:1 Mentorship · Fast Support
Companies are looking to data to make better business decisions, whether it is forecasting revenue, iterating processes for efficiency, or finding ways to increase productivity. This had led to employers seeking trained individuals who possess technical and data analytic skills, problem solving skills, and effectively communicate insights. Join our Data Analytics bootcamp and get the hands-on skills you need to launch a career as a data and business analyst. Learn how to query, clean, wrangle, analyze, and visualize data with modern tools that employers look for, such as Python, Pandas, Numpy, Matplotlib, SQL, Tableau, Jupyter Notebook, Selenium, BeautifulSoup, and more. Be trained in programming, databases, exploratory data analysis, web scraping, application programming interfaces, and how to implement strategies to efficiently communicate data-driven insights in a verbal and visual way.
Learn the relevant skills and modern tools you need to become a Data Analyst.
Put your programming and database skills, data analysis skills, and statistical techniques to work by taking raw data and turning it into information and insight for business decision-makers. Use modern tools used by professionals to extract data from sources, cleanse data, manipulate data, and visualize data.
Be surrounded by a support system of instructors that will answer your questions and meet with you 1:1 to provide direction on projects and mentorship throughout the program.
Get completed versions for all projects you can compare your work with to see what you did well and where you can improve so that you can strengthen your data analysis and visualization skills.
The demand is high for Data Analysts, Business Intelligence Analysts, and Data Engineers. Every company deals with data, but the need for someone who is trained in querying data, cleaning data, wrangling data, interpreting data, and visualizing data is growing. The ability to use programming languages and statistical tools to identify, analyze, and interpret patterns in complex data sets translates to great opportunities and a high career ceiling that has the potential to lead to high career earnings long term.
Knowing how to work with data and visualize it in a way that provides insight to business decision-makers means opening the doors to a flexible career path in which you can work in person or remote for startups, agencies, or large corporations. The more experience you gain the more growth and employment opportunities that will appear.
The technology industry and the way companies deal with data is evolving, which has led to an increased need for people who have a modern skillset that can work with data. Having a team of trained professionals who can take raw data, transform it into useful information, and visualize it for others to make better business decisions is what could lead a company to great profits. With data evolving and becoming more important than ever, the need for trained data analysts is increasing.
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Everything you can get by taking the Software Development program:
The Flex Self-Paced Software Development program continues where other seemingly similar programs end. Why? The modern software developer is now expected to know several different technologies including programming languages, libraries, and frameworks that are used with those languages, relational databases, backend development, and frontend development. This is why our curriculum is packed full of great content and value to prepare you for the role as a modern software developer.
Python is one of the most in-demand programming languages for data manipulation, data analysis, and data visualization. It is a skill that is a top priority to learn for any data analyst. In this module, you will learn the fundamentals of Python, intro to how to solve complex business problems with Python, data structures, problem solving, critical thinking, and the importance of version control with Git and GitHub to ensure your code is stored safely.
To get a job in data analytics, it is critical to know Structured Query Language (SQL) and how to query and handle data in relational databases. This makes SQL an invaluable skill in modern data analytics. In this module, you will learn how to use tools to connect to and query data from a database, how to write effective SQL queries, and how to select, group, analyze, and manipulate data across multiple tables.
Data cleaning is the process of correcting inaccurate data and removing inconsistencies. Data wrangling is the process of mapping and converting data from one format to another. Both are required skills to be a professional data analyst. You will learn data cleaning, data manipulation, and data wrangling with tools such as Microsoft Excel, Pandas, and NumPy.
Data analysis is the process of gathering, cleaning, analyzing, transforming, and modeling data with the intent of forming better business decisions. In this module, you will learn data analysis, statistics, linear regression theory and application, and take a deep dive into exploratory data analysis by learning how to identify a business problem, analyze data sets, manipulate data sets, and visualize data sets with Python and SQL tools.
A necessary skill that employers look for is the ability to visualize data. The purpose is to display a better understanding of data-driven insights and help decision-makers identify patterns. You will learn how to visualize data with Python libraries Seaborn and Matplotlib. You also will learn Tableau, a visual analytics platform that is the industry-leading choice for business intelligence and presentation of data.
Web scraping is a valuable way for data analysts and business analysts to gather data for analysis. In this module, you will learn web scraping syntax, how to take that syntax to navigate HTML hierarchy and gather data. You'll also learn how to use tools such as Selenium and BeautifulSoup to successfully scrape data from the web and pull it into an application for data analysis, manipulation, and visualization.
An Application Programming Interface (API) allows for applications of code to interact with one another to transfer data from one resource to another. Querying data from an API is a valuable ability to have because it allows for a data- or business-analyst to use that generated data for analysis, data modeling, and data visualization.
In this module, you will learn how to develop frameworks to handle the business impact of analyzed and reported data, the importance of communicating technical points with other data analysts and explanations to decision makers, and how to implement strategies to efficiently communicate data-driven insights in a verbal and visual way. You will continue to learn industry tools for business intelligence, reporting, and data visualization.
From Retirement Representative to Data Analyst: How Jim Uses Data to Help Drive Company Goals
Make sure you have a dedicated work space, free of distractions. The tools you need are most likely already at your disposal:
We use modern virtual tools and technologies to interact with students:
