Are you considering a career in data science? With the world becoming increasingly data-driven, the demand for data scientists is growing rapidly. DataScientest gives us the scoop on what you need to know before getting started.
Becoming a data scientist is an exciting and rewarding career, but it’s not an easy journey. To ensure success, it’s important to understand what is required before starting a data science course. Whether you’re a beginner or a seasoned professional, here is what you need to know.
DataScientest courses offer state-of-the-art learning, lifetime career support, and are eligible for a plethora of funding options.
Many industries are slowly transitioning from a focus on qualitative data to a focus on quantitative data. With this transition comes a demand for data scientists. In other words, companies are realising that their success depends on the ability to process, analyse, and interpret large amounts of data.
Data scientists provide companies with the tools to do this. In fact, data scientists are often tasked with identifying and quantifying risks, making them critical to industries such as insurance, finance, and healthcare. In order to meet these changing demands, many data scientists have to find new ways to process and analyse data. This is where machine learning comes into play - this is an area that is growing at an exponential rate.
Due to the ever-changing data landscape, data scientists must continually learn new skills. Therefore, it’s important to understand what skills you need to become a data scientist.
Some of the most important skills include programming skills, statistical and mathematical skills, the ability to use tools such as Excel and SQL, critical thinking and analytical skills, an understanding of data storage and architecture, and communication skills.
Data scientists use a variety of tools in their work, so programming skills are essential. Popular programming languages used in data science include Python, R, and Java. Data scientists also use tools such as Excel, SQL, or Power BI. A strong foundation in statistics and mathematical concepts is helpful, as data science is very mathematical in nature.
To join a DataScientest course, you should have the equivalent of a bachelor level diploma in mathematics, statistics or science - this is to ensure you have a good understanding of the concepts discussed - but people with less formal qualifications are also welcome to apply.
The exact content of data scientist courses will vary, but they will generally cover the following areas:
DataScientest courses comprise 400 hours of instruction, including 280 hours for training and 120 hours to work on your own personal project. The training covers topics like programming in python, data visualisation, machine learning, big data, complex systems and AI.
When choosing a data science course, you will come across many different options. Unfortunately, not all of these courses are created equal. To ensure that you choose the best data scientist course, here are some things to consider.
While there are no strict prerequisites to start a data science course, it’s important to understand what skill sets you will need to progress. First things first, you need to make sure that you have enough time to complete the course. Most data science courses last between six and 18 months.
On top of this, most data science courses will require you to have at least some of the following:
While this will vary depending on the course you choose and your skill set, many students who complete data science courses are able to find employment as data scientists. Data science is a growing field, and many companies are looking to hire data scientists. Some of the most in-demand industries include insurance, healthcare, finance, government, and education.
You can also earn money as a freelance data scientist. While this is not as stable as a full-time job, it can be a great way to get your foot in the door and make connections.
All DataScientest students get access to a platform dedicated to career services from day one of their course, while career managers are on hand for anyone who wants to discuss their future options. Students also benefit from monthly careers workshops, and an annual recruitment fair.
As previously mentioned, data is ever-changing, and the field of data science is constantly evolving. To remain relevant in this industry, it is important to keep up-to-date with new trends. Fortunately, there are a variety of ways that you can stay up to date, including:
With the demand for data scientists growing, there are now many resources available to help you learn data science. There are a variety of online courses and in-person courses that you can choose from. There are also eBooks, podcasts, and video series that you can use to learn.
Online courses are a great option if you want to learn data science on your own time and from the comfort of your own home. They usually provide a syllabus, lecture notes, and readings. In-person courses are great if you prefer to learn in a classroom environment and have the added benefit of networking with other students.
DataScientest, a leading European institution, offers courses that combine the pros of each type of course: a state-of-the-art platform where you get to learn to code - by coding - and a remote classroom environment where you can challenge your classmates, chat with professors and carry-out a real-life project.
Their courses are certified by the prestigious University la Sorbonne, offer lifetime career support and are eligible for a plethora of financing options. Find out more by visiting the website.