February 20 | 5:00 pm to 7:00 pm

Date Science Graduate Showcase

General Assembly

When:
February 20, 2019 @ 5:00 pm – 7:00 pm
2019-02-20T17:00:00-05:00
2019-02-20T19:00:00-05:00
Where:
General Assembly
Cost:
Free
Date Science Graduate Showcase @ General Assembly
You’re invited to General Assembly’s hiring event to meet our latest cohort of Data Scientists/Analysts, who have honed their skills in General Assembly’s Programs. Hiring managers, recruiters, and anyone hiring Data Scientists are welcome. Think of this as a reverse career fair, where you can see participants’ final projects and talk individually with them. This is open house style, so come whenever you can and stay as long as you’d like – drinks are on us

Who you’ll meet: Data Scientist/Analysts skilled in gathering, storing, and organizing your data using a basic data science toolkit: SQL, Git, and UNIX. Data grads can perform visual and statistical analysis on data using Python and its associated libraries and tools, explore the differences between supervised and unsupervised learning through the application of various modeling techniques such as classification, regression, and clustering, and apply analysis and modeling skills to real-world data problems in fields like finance, marketing, and public policy.

2019-02-20 17:00:00 2019-02-20 19:00:00 America/New_York Date Science Graduate Showcase You’re invited to General Assembly’s hiring event to meet our latest cohort of Data Scientists/Analysts, who have honed their skills in General Assembly’s Programs. Hiring managers, recruiters, and anyone hiring Data Scientists are welcome. Think of this as a reverse career fair, where you can see participants’ final projects and talk individually with them. This is open house style, so come whenever you can and stay as long as you’d like - drinks are on us Who you'll meet: Data Scientist/Analysts skilled in gathering, storing, and organizing your data using a basic data science toolkit: SQL, Git, and UNIX. Data grads can perform visual and statistical analysis on data using Python and its associated libraries and tools, explore the differences between supervised and unsupervised learning through the application of various modeling techniques such as classification, regression, and clustering, and apply analysis and modeling skills to real-world data problems in fields like finance, marketing, and public policy. General Assembly

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