Data Science Bootcamps
According to IBM, by 2020, the data analysis workforce will grow by 28% and the number of roles will increase from 364,000 to 2.7 million. For data science and other advanced data roles, the demand will reach 61,800. The democratization of data has governments, businesses, and organizations measuring any and everything to make better business decisions.
How Does Data Science Differ from Data Analytics?
Data Science is a cross-disciplinary field requiring skills in Computer Science (Machine learning), Statistics and Mathematics. Typically, it requires candidates to have an advanced degree in a STEM field (e.g., Science, Technology, Engineering, Mathematics, Statistics) and a good understanding of the sophisticated concepts underlying modeling. Most Data Scientists use R and/or Python as their primary tools.
Data Analytics is considered more entry-level and focuses on BI (business intelligence). Its focus is to draw business insights from commonly seen data types. It includes data cleaning, data visualization and simple modeling including linear regression. Common Data Analytics tools are SQL and Excel.
Why Choose a Data Science Bootcamp?
Data science bootcamps are largely known for being fast-paced and hands-on. Programs like Galvanize are built to help students master their skills in a pre-professional setting, surrounded by high-achieving peers. If learning by doing is something you seek in your data science education, a bootcamp may be worth it for you.
Data science bootcamps are generally geared towards students with some expertise in mathematics and coding. If you’re a coding novice, a data science bootcamp may not be worth it for you. At least not yet.
However, that doesn’t mean you can’t start on your journey. Galvanize offers data science prep courses that help students master Python fundamentals before enrolling in a formal data science bootcamp.
Data science also requires the use of analytics tools, technologies and languages to help data professionals extract insights and inform organizational strategy. In addition to professional bootcamps, there are other data science courses and training to better acquaint you with the tools and technologies employed by data scientists today.
Duration and cost of data science bootcamps varies greatly. Some last less than a week, while others can be six-months long. There are online data science bootcamps that cost less than $1,000; the most expensive exceed $15,000
Data scientists are driving the future of analytics. Traditional technologies are holding them back. Traditional data warehouses and big data tools are restricting the amount of data that can be stored and analyzed, and limiting the number of people that have access to data.
The Snowflake Data Cloud was designed from the beginning to efficiently integrate and support the applications that data scientists rely on. Unlimited data storage and compute resources can elastically scale to meet any need. With close integrations to machine learning-driven Spark, R, Qubole, and Python, it truly is the keystone in every developers dream stack.
Snowflake Snowpark delivers performant, elastic, and secure data processing in Snowflake using your language of choice, whether Python, Scala or Java.
Free Snowflake Program for Data Scientists and Analysts:
Virtual Hands-on Labs
This hands-on workshop shows you how to drastically reduce time to insight, scale up or down instantly depending on need, and analyze all your data from all your sources with Snowflake. Learn how to set up a data warehouse in practically no time and start receiving the actionable insights your business needs. Find a workshop near you.