What does a Data Analytics course teach you?
We are currently experiencing significant transformations in our world. The digitisation of the economy has led to the replacement of numerous jobs by technology-driven skills, a trend that shows no signs of slowing down. In such a landscape, traditional education methods have become outdated, unable to meet the requirements of tech companies. Consequently, new approaches to training, such as our Data Analytics course, have emerged to bridge this gap and cater to the evolving needs of the industry.
The idea of a coding bootcamp is still relatively recent. The first ones spontaneously appeared around 2013 in coworking spaces in New York, San Francisco, and Boston. However, you can now find coding bootcamps in almost all major cities around the world. Ubiqum started in Barcelona in 2016 as the first bootcamp in Europe to offer a Data Analytics program. Thus, our first cohort already has more than eight years of professional experience!
A bootcamp is a specialised, accelerated and professional learning process that helps people change their professional career completely. They give you real-world experience working on high-demand. digital skills and knowledge, such as web and mobile application development and data analysis and machine learning.
In this article we’re going to focus on how our Data Analytics program works and inform you about the course and the doors it opens for you.
What is Data Science?
When we started at Ubiqum in 2016, the popular idea of Data Science was very new and today there is still some confusion. So let’s start then by clarifying some of the professional pathways within the world of Data Science. We can distinguish three overarching, complementary roles:
1. Data Engineer
A data engineer is a professional responsible for designing, constructing, and maintaining the architecture and infrastructure needed to support and manage large amounts of data. They work with various data sources, such as databases, data lakes, and data warehouses, to ensure that data is collected, stored, and processed efficiently, securely, and reliably.
Key responsibilities of a data engineer include:
- Data Pipeline Development
- Database Architecture.
- Data Integration
- Data Transformation and ETL (Extract, Transform, Load)
- Data Quality Assurance
- Data Security and Compliance
Data engineers typically possess strong skills in programming languages like Python, SQL, or Java, along with expertise in working with big data technologies such as Hadoop, Spark, Kafka, and various database management systems. They also need a solid understanding of data modeling, software engineering principles, and cloud platforms where data may be stored and processed, such as AWS, Azure, or Google Cloud Platform
2. Machine learning Engineers
Secondly, we need people who develop algorithms. These algorithms are very complex software programs and require a great deal of expertise. A ML Engineer, as described here, is a software engineer on steroids.
A Machine Learning Engineer is a professional who specializes in designing, building, and implementing machine learning models and systems. They possess a strong understanding of software engineering, maths algorithms, data structures, and programming languages, enabling them to develop software complex and sophisticated software programs that we call Machine learning Algorithms.
This specialisation requires between 10 and 15 years of work and training and possibly a PhD that focuses on the development of a new machine learning algorithm.
3. Business Data Analyst
Finally, we have the person who analyzes and leverages data to improve businesses.
These three profiles combined compose what we know as Data Science: Data Engineering, Machine Learning, and Business Data Analytics.
At Ubiqum, we teach about Business Data Analytics in all of our Data Analytics & Machine Learning programs.
Beyond the Traditional Bootcamp
Since our establishment in 2016, we’ve undergone a significant evolution. Initially employing a conventional bootcamp format, where cohorts of 10 to 20 individuals progressed collectively, we’ve transitioned to a more adaptive and personalized model. Our primary objective is to cater to the diverse time commitments of our students by offering a bespoke mentoring service.
Our methodology is centered on real-world, very structured projects, designed to simulate the challenges professionals encounter in the business and corporate realm. This approach is further bolstered by the support and guidance from a dedicated personal mentor, coupled with the flexibility embedded within our program schedules.
- Intensity. Our courses cover extensive content within a short duration, allowing for rapid progress.
- Focus. We prioritize delivering highly specific and market-demanded content for tangible skill enhancement.
Personalisation: A dedicated personal mentor available throughout the course, providing one-on-one guidance.
Flexibility: Customized timetables and dedicated support tailored to each student’s requirements.
Practical and Professional : Emphasis on real professional practice over extensive theory, ensuring hands-on, industry-relevant learning experiences.
Fixed Timetables: Uniform schedules applied to all participants.
One Teacher for Multiple Students : Single instructor managing multiple students simultaneously.
Rigid Start and End Dates: Firmly set commencement and conclusion dates for the course.
Explore Ubiqum’s Data Analytics Courses
We provide three distinct career paths tailored to suit different student’s profiles.
- Data Analytics and Machine Learning: This main program prepares students to start as junior Business Data Analysts in the field. It’s suitable for anyone looking to kickstart a career in this area.
- Data Science and Deep Learning: An advanced program designed for students with a solid technical background (STEM) who want to delve deeper into the field of data science.
- Data Analytics and Power BI: Tailored for students inclined towards business aspects rather than the technical complexities. It focuses on mastering data management, modeling, and expertise in Business Intelligence using Power BI.
All our students attain proficiency in Python, SQL, modelling, and commonly used Machine Learning algorithms regardless of the chosen program.
Want to know more about our Data Analytics Courses?
We trust that this concise information has shed light on what you can anticipate from our bootcamp and how it will assist you in growing within the realm of Data Science.
For more information, fill out the form below and one of our career advisors will contact you with the complete syllabus and any further information you need.
Experience firsthand the Data Analytics Course at Ubiqum by taking advantage of our two-week free trial.
This trial allows you to immerse yourself in the course before making a formal commitment to enroll.