Intro to Data Analytics
Course
Contents
Unsure if data analytics is right for you? Are you curious, and want to know more? Or perhaps you just want to broaden your skillset or take your job to the next level? No matter your motivations, this 4-week course provides a thorough yet manageable introduction to all things data. It will help you discover the practical details of using and analyzing data to make better decisions as you deliver your first data analysis project.
1. Who is the course for and what are the requirements? 3
2. What will you finish the course with? 4
3. What kind of support is available? 5
4. How much time do you need to commit to the course? 6 5. What is the structure and format of the course? 6
6. Course outline 8
7. What kind of project will you be working on? 9
8. Tuition and payment 10
9. Application and enrollment 10
What you’ll get
Regular calls and unlimited messaging with your tutor and mentor
A video review of your project by your mentor for expert advice as you develop your
portfolio
14‑day trial period
Get your money back if the course isn’t right for you
Flexibly paced
A 15-hour/week pace can be organised around any schedule
Lifetime access to our curriculum Get access to more than 80 hours of curriculum written by expert data analysts Active online student community
Find a study buddy through online and in-person meetups
If you’re interested in data analytics, but want to get a taste of what it’s like to work as a data analyst before you make the leap—we’ve got you covered! The Intro to Data Analytics Course is the perfect solution for those brand‑new to the industry and a great way to see whether data analysis is right for you.
You will primarily work with Excel, so if you don’t have it already, you’ll be able to sign up for a trial that will last for the duration of the course. Excel continues to be an essential tool for data analysts to quickly access, organize, and manipulate data in order to generate insights.
It’s a versatile tool for conducting analyses in a wide variety of contexts and businesses. Aside from that, you’ll be working with your preferred presentation software (Microsoft Powerpoint, Google Slides, or Apple Keynote).
1. Who is the course for
and what are the requirements?
2. What will you finish the course with?
This course will walk you through the day‑to‑day work of a data analyst as you go through the complete process of analyzing a dataset and work towards presenting your first case study. By the end of the course, you’ll have the practical and technical skills necessary for applying this process to other projects.
You’ll start by drawing initial conclusions from a set of data to make hypotheses and present that data to stakeholders. You’ll then explore the role a data analyst plays in a team and in a company, as well as
Excel Minimum Requirements
Operating system macOS: Intel processor Monitor resolution 1280 x 800
Disk space 10 GB of available disk space; HFS+ hard disk format (also known as macOS Extended) or APFS
RAM 4 GB RAM
System and hardware requirements
In terms of hardware, you’ll need a computer or laptop for the course (Mac or Windows). Here are the system and hardware requirements for the main tool you’ll use in the course, Excel.
macOS
Windows
Excel Minimum Requirements
Operating system Windows: 1.6 GHz or faster, 2-core Monitor resolution 1280 x 768
RAM 4 GB RAM
You’ll use Excel—one of the primary tools used by data analysts—to quickly access and generate key insights from data; how to sort, filter, format, and organize a dataset; how to analyze and describe your dataset—where it came from, how large it is, what it covers, and what’s missing; how to clean and identify sources of error in your data; how to aggregate data, modify your dataset, and use pivot tables;
how to apply different analytical approaches such as descriptive, predictive, and diagnostic; and how to apply statistical methods to your dataset.
You’ll also learn how to form hypotheses around how a dataset will look and generate useful insights about the data, how to build helpful visualizations of your data to present your findings to stakeholders, and how to tell a compelling narrative around old and new assumptions and insights into a business problem. You’ll also be able to communicate your findings to others effectively and inform the important decisions being made around you.
If you complete the Intro to Data Analytics Course and decide that you’d like to transform your career, you can upgrade to our full, 8-month Data Analytics Program (job guarantee included) and receive a tuition credit.
3. What kind of support is available?
Your tutor
is your course specialist, providing feedback on your daily submissions and answering any questions that come up about individual tasks or instructions. Every time you submit an assignment, you can message back and forth with them via the messaging tool on our platform.
Student Advisors
ensure you have the best possible
experience throughout the course. You can message them from your dashboard (within the platform)—they’re always happy to answer any questions you have about the administration of your course.
As part of the course, you’ll receive support from your dedicated tutor and mentor, your student advisors and a community of fellow learners.
Fellow students
As a CareerFoundry student, you’ll be part of an extensive community of fellow students both during the course and after graduation. You can reach out to your fellow students to discuss your program, organize meetups, or find a study buddy via Slack (instant messaging tool). As a part of our graduate community, you’ll have lifetime access to our Slack workspace so that you can stay in touch with your fellow graduates. Our students also regularly organize in-person meetups around the world, where they network and share experiences.
Your mentor
is a seasoned and influential data analyis expert we’ve hand-picked to provide industry insights and guidance to help you succeed in your chosen field. They’ll also do an in-depth video review of your portfolio project at the end of the course.
4. How much time do you need to commit
to the course?
Our Intro to Data Analytics Course takes about one month to complete. Since you’re not required to be online at specific times to work on the material, you have a great deal of flexibility in which hours you set aside for study.
The course requires an average of 15-20 hours per week—though this may vary depending on the time you need to understand course material and learn various industry standard tools. It’s also possible to finish the course in less than one month. Some students put aside time specifically to complete their course, dedicating an average of 30-40 hours each week for a total course duration of 2-3 weeks.
5. What is the structure and format
of the course?
The course provides a 100% asynchronous online learning experience that is flexibly‑paced—so while there is an overall completion deadline, you get to decide how to fit your study hours around other obligations. Our curriculum is built with the beginner in mind, but it is comprehensive and rigorous—
created in‑house by our team of curriculum designers, and authored in collaboration with industry experts.
Your tutor will give feedback and approval for the first seven tasks in the course. For the eighth and final task, you’ll submit your work to your mentor for a final review of what you’ve completed throughout the course. There is no final exam at the end of this course. It’s counted as complete once all the exercises have been reviewed and approved by your mentor. You’ll be able to download your certificate of completion directly from the dashboard.
If you’re curious about how it will all look, take a tour of the CareerFoundry learning dashboard
Intro to Data Analytics
Learn how to prepare and analyze data: Develop critical skills to interpret business requirements that guide your data analysis.
6. Course Outline
1. Data Analytics in Practice
Learn what data analysts do, what tools they use to process data, and how they apply their skills in different industries.
Prepare to kick off your own analysis by getting familiar with the dataset you’ll be working with in your course project.
2. Introduction to Excel
Get hands-on with Excel, one of the primary tools used by data analysts to quickly access and generate key insights from data. Learn how to sort, filter, format, organize, and create useful visualizations from a dataset.
3. Understanding Your Data Set Analyze and describe your dataset—
including where it came from, how large it is, and what’s missing—in order to identify sources of bias and better understand how it relates to the problem at hand.
4. Cleaning Your Data
Identify sources of error in your data, and learn how to clean your dataset to minimze potential issues.
5. Conducting a Descriptive Analysis Apply statistical methods to your dataset using Excel to complete a thorough descriptive analysis.
6. Developing Insights
Form hypotheses around how a dataset will look, and generate useful insights about the data by comparing the behaviour of the data to your first estimates.
7. Visualizing Data Insights
Build helpful visualizations of your data to present your findings to
stakeholders. Based on the type of data you are working with, choose the most effective visualization for the problem you’re trying to solve.
8. Storytelling with Data
Present the results of your analysis to others, providing a compelling narrative around old and new assumptions, and insights into a business problem.
Everything you do in the course will lead you toward completing a project that you can proudly showcase in your professional portfolio. For your course project, you’ll build an end-to-end analysis for a video games dataset. Along the way, you’ll learn about and create some of the essential deliverables employers and teams need.
The dataset you’ll build will help a new video game company refine their understanding of how new games might fare in the market. You’ll finish the course with a full case study and presentation of your findings, which will be carefully polished with the advice and input of your tutor and mentor.
Your final deliverable for the course will be an Excel workbook with multiple sheets containing all of your different data manipulations and analyses. You’ll calculate summary statistics for different variables, create visualizations for your data, develop insights and give recommendations to hypothetical shareholders, and even present your findings like a data analyst in a real company.
Once you’ve completed the course, you’ll be able to use your project as a complete case study, including effective visualizations and a presentation, to showcase your data analysis skills to potential employers.
Here are some examples of student projects from this course:
7. What kind of project will you be working on?
See project See project
Viktorija Juskevica CRM Manager
Patrick Shaughnessy Cybersecurity teaching assistant
8 Tuition and payment
9. Application and enrollment
We don’t require you to go through any long-winded application process in order to participate in a CareerFoundry course or course.
We know that our students can change careers successfully, regardless of their background.
If you’d like to make sure you’re familiar with all of the details before signing up, get in touch with us .
Ready to dive into data? Enroll in the course now. We can’t wait to see you in the course!
We offer you the chance to try out the course for a period of 14 days. This begins on the course start date. If, within that time frame, you decide that the course is not for you, we’ll refund 100% of any tuition you’ve paid.
If the 14-day trial period has passed and you’d like to withdraw from the course before 60% of the course time has elapsed, you get a prorated refund based on remaining course time. See the full terms and conditions on our website.
You can view the price for the course directly on the CareerFoundry website . We currently accept payments by credit card, Paypal, and bank transfer.
