DATA SCIENCE MANAGEMENT CERTIFICATE

DATA SCIENCE MANAGEMENT CERTIFICATE

Managing a team of Data Scientists can be tough. Often the most talented Data people think, and act, in a “non-traditional” manner. Expecting a data team to work like a typical 9-5 employee can be disastrous. Managing these unique individuals takes a special skill set.

 

In this certificate, you’ll learn not only how to think like your team, but how to empower them to innovate and excel at their jobs. You’ll also learn how to communicate in a manner that completes the task(s) at hand but allows for creative problem solving as well.

 

Finding Data Science people can be tough. Retaining those people can be even harder.

Once a (good) data science person finds the right fit with management and work environment,

they stay for a long time.

Certification Requirements

Prerequisite:

MUST BE IN THE ROLE of a Data Scientist (or equivalent) for at least 1 year with aspirations of future management

 

OR

Complete ALL of the following:

Data Visualization Certificate

Fundamentals of Data Visualization (Tableau 101)

3 hour sessions, two days/week for 4 weeks
In this class, students will learn the fundamentals of expressing data visually using Tableau. We will teach you data design and how humans digest data–specifically, the fundamentals of data visualization design and construction, as well as best practices needed to implement them. This class uses Tableau, an industry-wide benchmark for quality visualization tools.

Tuition: $1,650 

Power BI – Business Intelligence (BI 101)

3 hour sessions, two days/week for 4 weeks
Power BI is a major tool for most Data Analysts to use in Data visualization, especially when the data needs significant preparation prior to visualization. This class will teach how to visualize data using Power BI and how to collect, arrange, and prepare data for visualization.

Tuition: $1,650 

BI Analyst Certificate

Introduction to Python Programming (Python 101)

3 hour sessions, two days/week for 4 weeks

In this class, students will be introduced to some of the major concepts of Data Science (Python Programming, Database Management, Modeling, and Data Visualization) and some of the tools used in the profession. The tools include a crash course in the basics of programming, data structures and object oriented design, basic web development, Jupyter Notebooks, GitHub, and web scrapers, as well as functional programming concepts and key Python libraries (Numpy and Pandas). This module, taken individually, does not earn a student a certificate.

Tuition: $1,650 ($1,500 when also taken with SQL 101)
 
Data Manipulation and Management (SQL 101)
3 hour sessions, two days/week for 4 weeks

This class teaches a student how to store and transform data specifically to be used in modeling. Students will learn database design, SQL queries, different schemas, data cleaning techniques, and data appending. The class also will introduce a tool called Dataiku, a data platforming tool used for easier data engineering and visual/drag and drop data science. This module, taken individually, does not earn a student a certificate.

Tuition: $1,650 ($1500 when also taken with Python 101)

Machine Learning Certificate

Basic Model Building (Model 202)
3 hour sessions, two days/week for 4 weeks

Fundamentally, data science is using statistics and economic modeling to predict what is likely to happen next. This class will teach the student the fundamentals of how to build common algorithms inside of an industry-leading data science platform called Dataiku. This will include the basics of model evaluation, choosing target variables and characteristics, and basic machine learning. This module, taken individually, does not earn a student a certificate. This module, taken individually, does not earn a student a certificate.

Tuition: $1,650 ($1,550 when also taken with Eval 202 and Python 202)
 
Mathematics of Model Evaluation (Eval 202)
3 hour sessions, two days/week for 4 weeks

This class will dive into the metrics behind evaluating an analytics model’s performance using F1, Accuracy, Precision, Recall, AUC, Cost matrix, and Cumulative Lift. Students also will learn to show the steps to building, testing, evaluating, adjusting/rebuilding, re-testing, and re-evaluating a model. Finally, students will learn which model to use, avoiding the pitfalls of just using accuracy as an indicator. This module, taken individually, does not earn a student a certificate.

Tuition: $1,650 ($1550 when also taken with Model 202 and Python 202)
 
Advanced Modeling in Python (Python 202)
3 hour sessions, two days/week for 4 weeks

Data science has gone from needing to know how to code to most modeling techniques having standardized libraries that can be pasted into a program. This means that one may do data science without understanding what the models mean or actually do. This class will drill into how to program models the traditional way. Students will use Word2Vec to scrape, debug, and enhance data science models. They also will learn how to use Python to solve other gaps such as calculations, other data manipulation, and random number population. This module, taken individually, does not earn a student a certificate.

Tuition: $1,650 ($1550 when also taken with Model 202 and Eval 202)

Complete the following:

3 hour sessions, two days/week for 4 weeks

Data Scientists are a new type of employee and require a new type of leadership, understanding, and management. Taught in workshop format alongside the book, “Leading a Data Driven Organization – A Practical Guide to Transforming Yourself and Your Organization to Win the Data Science Revolution,” this class walks through the concepts of data science to equip students to succeed as leaders in the field.

Tuition: $2,500 

Total Time/Cost to complete certification:

4 weeks/$2,500 if you have the necessary prerequisites

What does a Data Science Manager do?

A DATA SCIENCE MANAGER manages the design and implementation of big data solutions for the organization. They also oversee the team responsible for predictions, models, visualizations, APIs, and databases associated with the models. They typically report to C-Suite.

Common tasks of a data science manager:

  • Creating and managing repositories for data inside the organization
  • Manipulate that data to better analyze.
  • Build and manage models to predict outcomes
  • Research potential issues and insight inside the data
  • Present findings to non-technical leadership and/or users about their findings
  • Implement those models/findings into the enterprise for automation and use at scale.
  • Manage Data Science team, including staff development
  • Oversee model selection, model implementation, and management
  • Present findings to C-Level executives.

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OMAHA DATA SCIENCE ACADEMY

2112 N.30th Street
Omaha NE, 68111