Introducing the Anaconda Data Science Certification Program


There is strong demand today for data science skills across all sectors of the economy. Organizations worldwide are actively looking to recruit qualified data scientists and improve the skills of their existing teams. Individuals are looking to stand out from the competition and differentiate themselves in a growing marketplace.

As the creators of the world’s most trusted Python data science platform, we at Anaconda understand the challenge of identifying truly qualified data scientists. To meet this challenge, we are pleased to introduce the Anaconda Data Science Certification program!

This program provides opportunities for data scientists to jumpstart their careers with a proven, structured learning path, and also offers organizations the ability to qualify their data scientists to an independent standard. Achieving Anaconda Data Science Certification demonstrates that an individual exhibits the skills and expertise necessary to work as a Python data scientist in any sector.

Drawing from our own in-house experiences—as well as from industry-leading “Friends of Anaconda”—our experts have distilled the main elements of a professional data science skill set into a carefully crafted, seven-topic Data Science Certification Path. For each certification module, individuals will be administered a proctored, two-part exam. Passing an exam makes one Anaconda Certified (AC) in that area. To earn the Anaconda Certified Professional (ACP) – Data Scientist designation, individuals must pass all seven module exams and also complete a comprehensive exam.

Anaconda Data Science Certification Path:

  1. AC – Anaconda Foundations: Individuals must demonstrate the ability to configure a simple computational environment with minimal computational resources.
  2. AC – Data Import & Export: Individuals are required to access and manage data on a local machine or on remote computing resources.
  3. AC – Data Manipulation & Analysis: Individuals must demonstrate the ability to clean, organize, and analyze data.
  4. AC – Data Visualization: Individuals must demonstrate the ability to visualize data and prepare it for presentation.
  5. AC – Statistical Analysis & Inference: Individuals must demonstrate the analytical skills to interpret and understand volumes of data meaningfully.
  6. AC – Machine Learning: Individuals are required to understand and apply common frameworks for machine learning.
  7. AC – Data Science at Scale: Individuals are required to apply all the skills described above in a big data context.

The ACP – Data Scientist designation is the comprehensive, industry-standard certification for data scientists. To qualify, you must first complete the seven modules above. Once completion of the seven modules is verified, you are eligible to take the comprehensive examination, which will cover all the steps in the Data Science Certification Path. Passing the comprehensive exam will earn you the official title of Anaconda Certified Professional (ACP) – Data Scientist.

To prepare you for these exams, we recommend learning directly from the Python experts! Anaconda is proud to partner with DataCamp for a series of interactive data science training courses that correspond with our Data Science Certification Path. DataCamp is the foremost leader in Data Science Education, pioneering technical innovation and offering skill-based training and courses from the world’s best educators.

Anaconda’s unique position and expertise in Python data science enables us to establish a state-of-the-art benchmark for what it means to be a data scientist today. Contact us anytime to learn more about the Anaconda Data Science Certification.

We will be offering other learning paths and corresponding certifications soon—stay tuned!

You May Also Like

Data Science Blog
Anaconda Debuts Data Science Certification Program
Certification to Standardize Data Science Skill Set among Employers and Professionals AnacondaCON, Austin, TX—April 9, 2018 — Anaconda, the most popular Python data scien...
Read More
Data Science Blog
Intake: Taking the Pain out of Data Access
By Martin Durant, Anaconda Software Engineer We are pleased to announce the release of Intake, a simple data access layer and cataloging system. This article contains code exe...
Read More
Data Science Blog
Introducing Skein: Deploy Python on Apache YARN the Easy Way
By Jim Crist *This post is reprinted with permission from Jim Crist’s blog. The original post can be found here.In this post, I introduce Skein, a new tool and library...
Read More