Practical introduction to information analysis and exploitation: From 0 to data analyst
Learn the two most widely used levels of analytics in organizations—descriptive analytics and predictive analytics—and their potential applications. This will allow you to gain practical knowledge by making your first implementations with industry-standard tools. Begin your journey to start working in the data industry.
Introduced role:
Data Analyst
This course will allow you to gain practical knowledge by performing your first implementations with industry-standard tools. You will receive training that will prepare you for real-world work as a data analyst.
How will this course transform you?
The student, without prior exposure to the world of data, will learn what they need to begin working on their first data analysis and mining projects in 10-12 hours.
When they finish, they will be able to use their knowledge for real-world projects and begin their journey in the world of data at any company that makes the effort to mentor them.
How will we do this?
Looking into the curriculum in detail:
Module 1:Introduction to data collection and analysis
This first module is designed to be the first contact with the world of analysis, it provides the necessary basic knowledge of business, technology and statistics, explains to the student what information needs to be collected as a minimum for commercial purposes, and the ways in which it can be used.
Module 2: Introduction to data engineering and architectures
If in the previous module we explained everything necessary to the student to get started in the world of data collection and analysis, in this chapter we will introduce everything necessary to understand how data is stored. We will discuss cloud technology and the different types of information systems that exist.
Module 3: Introduction to descriptive analytics and its practical application with SQL
Once we've seen how to collect and store information, we can begin to understand how to use it. This module will be an introduction to SQL for descriptive analytics. It will provide an introduction to descriptive analytics using SQL as the main example tool, and will teach students the fundamentals of database management.
Module 4: Introduction to descriptive analytics and its practical application with PowerBI
We continue to refine our knowledge of descriptive analytics with the following tool. This module will be an introduction to Power BI for descriptive analytics. An introduction to descriptive analytics will be provided using Power BI as the main example tool, and students will be taught how to use its components.
Module 5: Introduction to AI Engineering and Predictive Analytics
Introduction to how machine intelligence works, the types of artificial intelligence that exist, and the types of projects typically seen in predictive analytics.
Module 6: Practical application of predictive analytics with Google Collab
First introduction to predictive analytics using Google Collab and its automatic code generation tool. This will allow students to see what more advanced algorithmic development work looks like, using real code.
There are AIs that work with little code (as seen in Module 3). In this chapter, we allow students to see what it's like to train an AI algorithm with the usual amount of code. For this, we'll use an example of a pre-prepared notebook execution, giving them the opportunity to run and explore it. They'll be able to generate code without any programming knowledge thanks to Google Collab's AI tool, which automatically creates code.
What will you be able to do after finishing this course:
You'll be able to conduct an initial assessment and diagnosis of the analytical quality of any company you work for, enabling you to propose improvements up to at least a solid and profitable basic level.
You'll be able to develop your own data projects within your budget based on these identified improvements, and begin implementing them with the technologies discussed in the course (PowerBI, Google Collab, AWS).
You'll be able to begin learning, through self-study, how to implement these projects as you work on them on your own.
Price: 450 euros
The price includes necessary sessions to deliver the course ( 4 to 6), doesn't include relocation for offline sessions. Online webinars have no additional costs.
Frequently asked
questions
Nope, we can help you build your data and math culture into your team, and help you recruit if you are starting from scratch. If you already have a team we can train them for you
Some of them are oriented to a more technical role in your data team, and others, like our data-driven team's, are focused on management and leaders that don't need to get down and dirty with code.
Depending on the quantity of work we are dealing with, or our internal experimentation, we have from time to time a beta-testing program where we allow lucky users to test a course, service, or workshop in exchange for feedback and, if satisfaction is achieved, a referral. Ask us about it to see if you apply.
Simple, our data-driven team's master program. It will teach you everything you need to get started and you will have 5 sessions with us to help land any concept you did not understand into your organization, it's by far the best program to transform an organization on the internet.