Data Analytics Classes Madrid

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 so students can refresh the material.

Data Analytics Flex is a 6-month part-time program designed to get you a job as a data analyst. You will begin by learning how to master Excel and tell stories with PowerPoint. Afterwards, you'll learn how to query data using SQL and visualize data using Tableau. Once you've mastered these building blocks, you'll receive business case studies to simulate real-world work projects, and you'll also be exposed to statistics. Finally, you'll learn how to clean data using Python and work on your capstone project. This program comes with a tuition-back guarantee if you don't land a job within 6 months of graduation.

In this program, participants will learn the key skills and tools needed to succeed as a data analyst, including Excel, SQL, and Tableau. Attendees will learn how to use Excel to create graphs, summarize data with PivotTables, and analyze data. In SQL, attendees will learn the essentials of relational databases, queries, functions, and more. Finally, participants will learn Tableau to create visualizations to present their data clearly. The program is open to beginners and has flexible scheduling options. Tuition includes hands-on training, a free retake, and training manuals for each course.

In this Data Analytics course, students will master Python, SQL, Looker (formerly Google Data Studio), Streamlit, and statistics, equipping them to join any data-driven team with proficiency in creating predictive models using Python and its powerful libraries like pandas and NumPy. The curriculum covers a range of algorithms, supervised and unsupervised learning models, real-life case studies, and industry-standard tools, along with comprehensive training in strategizing and developing AI projects from development to deployment, with a focus on privacy and security.

In this 8-day intensive Data Analytics bootcamp, students with little to no background in data analytics will learn how to use Microsoft Excel, SQL, and Tableau to summarize, display, and discover key insights hidden in data sets. By the end of this bootcamp, students will be able to use Excel to aggregate and summarize data, summarize and analyze data with PivotTables, create charts and PivotCharts in Excel, use SQL to filter and sort large data sets, perform advanced database queries, create visualizations with Tableau, and much more. Students will also be able to reinforce what they learn through the numerous projects they encounter throughout the course. This course also offers a free retake within six months to allow students to revisit any concepts needing to be refreshed and walk away with a much stronger grasp of the material.

Students build in-demand industry skills and prepare to take certification exams in Tableau and Amazon Web Services. The program consists of Fullstack’s live online classes and workshops so you will feel fully supported along your journey. The up-to-date curriculum ensures course activities are relevant to real-world applications, and interactive technology helps you master the knowledge and skills you’ll acquire throughout the program.

This data science program provides training in Python and its major data science libraries, data visualization tools, such as Power BI and Tableau, machine learning models, and cloud computing.

The three-day Python Data Science training program teaches students to evaluate and manage datasets using the Python programming language and software libraries such as Pandas. This course walks students through the process of creating data arrays from existing and new datasets and how to best visually represent these data.