What are the key skills to have if you want to become a data scientist in 2021?
Summary
A few years ago most data job ads requested a PhD, or at the very least a masters, in maths, statistics or a similar subject as an essential requirement.
Over the last couple of years, things have evolved. Companies are now hiring data scientists based on their ability to perform applied data science rather than research. Particularly outside of the tech giants such as Amazon, Facebook and Google.
“There is a saying, ‘A jack of all trades and a master of none.’ When it comes to being a data scientist you need to be a bit like this, but perhaps a better saying would be, ‘A jack of all trades and a master of some.’” Brendan Tierney, Principal Consultant at Oralytics.
What are the key skills to have if you want to become a data scientist in 2021?
1. Python
Learn programming in Python, how to work with Jupyter Notebook and to use powerful Python libraries like Pandas and NumPy to explore and analyze big data sets. Collect data from various sources, including CSV files, SQL queries on relational databases, Google Big Query, APIs and Web scraping.
Skills learned at Le Wagon Data Science Bootcamp:
-Using Jupyter Notebook -Loading and exploring a dataset -Extracting data from different sources -Pandas and NumPy -Google Big Query -Web scraping
2. Relational Database and SQL
Learn how to formulate a good question and how to answer it by building the right SQL query. This module will cover schema architecture and then dive deep into the advanced manipulation of SELECT to extract useful information from a stand-alone database or using a SQL client software like DBeaver.
Skills learned at Le Wagon Data Science Bootcamp:
-Database schema architecture -Translate a business question into a SQL query -Advanced manipulations of SELECT -SQL client software like DBeaver or Metabase
3. Data Visualization
Make your data analysis more visual and understandable by including data visualizations in your Notebook. Learn how to plot your data frames using Python libraries such as matplotlib and seaborn and transform your data into actionable insights.
Skills learned at Le Wagon Data Science Bootcamp:
-Turn your data into insights with data visualizations -Different categories of charts -matplotlib and seaborn
4. Statistic, Probability, Algebra Linear
Understand the underlying math behind all the libraries and models used in the bootcamp. Become comfortable with the basic concepts of statistics & probabilities (mean, variance, random variable, Bayes’s Theorem, etc.) and with matrix computation, at the core of numerical operations in libraries like Pandas and Numpy.
Understand the architecture of neural networks (neurons, layers, stacks) and their parameters (activation functions, loss function, optimizer). Discover a new library called keras, which is a developer-friendly wrapper over tensorflow, a Deep Learning library created by Google. We'll teach you the fundamental techniques to build your first deep learning model with Keras.
Skills learned at Le Wagon Data Science Bootcamp:
-Architecture of a neural network (neurons, layers, stacks)
-keras library
-tensorflow, Deep Learning library created by Google
Join Le Wagon and change your life in 2021! In 9 intensive weeks, learn Data Science from Python to advanced Machine Learning, code your own data applications and boost your career.
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