7 surprising facts about Data Science you didn't know about 💡
Discover 7 facts about Data Science and Digital Data, ''the oil of the 21st century''. The world’s demand in Engineering Jobs is booming especially in the UAE. Learn how Le Wagon Dubai seeks to meet this increasing need for Engineers to explore and analyse data by launching Le Wagon renowned Data Science Bootcamp in Dubai next April.
1. Less than 0.5% of all data we create is ever analysed and used.
With the rise of tech, cloud and open data there is a huge potential in analysing Data but this has only been exploited at a very small scale so far. With our renowned Data Science Bootcamp, Le Wagon seeks to meet this increasing need for new age Engineers to explore, clean, analyse and predict data. Our team of professional developers, data scientists and Machine Learning engineers passionate about education joined forces with Industry experts* and spent over a year building the course before launching it in 2020. By the end of the 9-week bootcamp Le Wagon students have learnt critical Data Science skills as well as how to build strong narrative around data and solve real business challenges.
*Instacart, Machine Learning Academy, Airbnb, STYCKR, Ava Accessibility and Resteo
2. According to LinkedIn, the world’s largest professional network, Engineering is in the top 15 job categories driving the UAE job market in 2021.
The world’s demand in Engineering Jobs is booming and this job category will be particularly in search for new talents in the UAE in 2021. Many companies in all sectors realize that investing in new technologies to collect, transform, understand and analyse data is key to survive in the future. In the “new normal” economy, tech roles will be one of the most crucial forces needed for the business recovery. According to a recent article by GulfNews, Engineering roles are among those ‘pandemic-proof’ job categories that UAE employers will be willing to hire this year. Le Wagon is proud to take part in the UAE’s digital transformation, and announce the official launch of its 9-week full-time Data Science Bootcamp this April 2021 in Dubai.
3. Data Science salaries are much higher than any other Tech development professionals.
Data roles are extremely versatile and working in Data Science requires a complex set of skills. From basic Maths – like Statistics, Probability and Linear Algebra – to more complex skills such as Python tools - including Python programming language, Jupyter Notebook, Python libraries –, Machine Learning and Deep Learning, Data Roles have multiple functions.
In fact, most of Data Engineers were first back-end developers. Many of our Data Science students attended our Web Development bootcamp or had knowledge of programming and Mathematics before attending this course. Such roles also demand to be able to work in teams and to know how to communicate about Data science models to non-tech employees. That is why we teach students the core concept and give them solid foundations but also make sure they learn how to collaborate in a tech team and how to communicate their findings to non-technical audiences. At the end of the 9 weeks Le Wagon’s students are market-ready!
4. Data Science is used across all industries and fields from art to healthcare.
Digital Data is ‘’the oil of the 21st century’’. There is so much existing data that there are infinite combinations of real-world applications in absolutely any kind of fields or industries: healthcare, trade, agriculture, communication, banking etc.
During the last two weeks of our Data Science bootcamps, students team up to work on a concrete project of their choice. For example, last October in Germany, a team of students built a tool to detect fake news, while another team created an art-price estimator. Last year in Paris, a team put together a model to predict the time spent in hospitals and the number of new patients, and another group successfully built a tool dedicated to cardiologists to detect heart arrhythmia.
Data Science has endless possibilities of use cases!
5. Data Analysts, Data Scientists and Data Engineers are not the same.
Data Analysts are the people closest to the business. They handle the raw Data, clean it to enable the Data Scientist to use it. They have very good knowledge of Excel, Data Visualization, Statistics and SQL, and Python.
Data Scientists take care of the Mathematical analysis of the Data. They use probability theory and algorithms to forecast results from discovered data trends and need experience in the sector or the industry they are working for to be relevant.
Data Engineers are very technical roles. They are compiling and ensuring the integrity of the Data. They deploy the application to properly receive, store and give access to the data for people who need it.
After our bootcamp, you can start applying for Python Data Analyst jobs or Junior Data Scientists positions. Depending on your level before the bootcamp, you can also start at a Junior Data Engineer position.
6. 75% of Data Experts use Python for Data Science Work.
The Python programming language was designed in the last 1980s and had plenty of time to evolve and to acquire a large and supportive community. Although it’s a high-level language and can do complex tasks, Python is one of the most accessible programming language with its simple syntax which gives more emphasis on natural language. During Le Wagon 9-week full-time bootcamp, our students learn how to code in Python and master other key Python-related tools such as Jupyter Notebook and Python libraries.
7. Data Science is at the crossroads of Computer IT, Mathematics & Statistics and Domain expertise.
Data Science is an inter-disciplinary field that uses a mix of mathematical, scientific and business skills. Our 9-week course covers all three fields ensuring your market-readiness by the end of the bootcamp.
Weeks 1-2: Data Science fundamentals. We cover the fundamentals of Python and Mathematics for data science. Week 3: Decision Science. You will learn how to prepare a set of data with Python and how to communicate your findings to non-technical audiences. Weeks 4-5: Machine Learning. In this module, you'll understand the different classes of machine learning diving into the most used library in Machine Learning: scikit-learn. Week 6: Deep Learning. We will cover the building blocks of Neural Networks and understand what the Neural Networks are made of and which parameters they rely on. Week 7: Data Engineering. You will learn all the best practices around experimenting with a real-world dataset and how to use machine learning to solve an exciting problem. Weeks 8-9: Data Science Final Projects. During those 2 last weeks, students work on a concrete data science project and present it during the Demo Day.
Click here to find out more about the courses in our detailed syllabus
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