Analytics for Data Science Certificate

This certificate program covers everything from forecasting and data visualization to network analysis, risk simulation, and a deep dive in predictive analytics.

Overview

Our Analytics for Data Science Certificate will give you the skills needed to understand, transform and model data to provide useful information to support informed decision-making. This ten course program – including eight required courses and two electives – covers the key analytical concepts and tools you need to help you manage, classify and interpret large data sets, to uncover hidden patterns, correlations, and other insights.

The core curriculum, taught by leading experts in this industry, covers everything from forecasting and data visualization to network analysis and risk simulation, with a deep dive in predictive analytics. Our certificate programs mix theory and practical application so you can apply your skills immediately at your current job or leverage them as you seek a new one.

SCOPE: Approx. 28 course credits in the U.S. academic system (most Masters programs are 30-36). These are transferable as college credit – via the American Council on Education – to other institutions in the U.S. See course offerings below.

Who This Certificate Serves

If you are working in data science, or are aiming to be a data scientist, there's good news: according to online recruiting sites, "Data Scientist" ranks as the best job in America for the past four years. If you need to add data mining to your skill set, or are responsible for analytics teams or vendors, or simply want a deeper dive in data analytics, this certificate program is designed for you. Professional titles of interest are:

Data Analyst
Business Analyst
Data Scientist
Statistician

Researcher
IT Professional
Marketing Operations Manager

Learning Outcomes

With a Certificate in Analytics for Data Science, you will learn the concepts and skill to be a productive member of an analytics or data science team, or to work closely with those teams, without having to become a dedicated programmer. Specifically, you will learn how to:

Choose and fit time-series forecasting models
Construct predictive models using a variety of statistical and machine learning algorithms, and assess their performance
Identify customer segments and generate purchase recommendations
Solve constrained optimization problems using linear programming and other techniques

Use interactive graphical techniques to visualize and analyze data
Conduct Monte Carlo simulation to account for risk
Specify and solve queuing problems
Analyze location and other spatial data (elective)
Apply the key concepts in natural language processing (elective)

Prerequisites

You should be familiar with introductory statistics; if needed we can enroll you in Statistics 1 and Statistics 2 at no charge.

Required Courses

The Analytics for Data Science Certificate program consists of ten 4-week courses offered completely online at Statistics.com. Below find the eight required courses you will need to take:

Forecasting Analytics

This course will teach you how to choose an appropriate time series model: fit the model, conduct diagnostics, and use the model for forecasting.

Topic: Analytics, Prediction/Forecasting | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 10, 2020, Nov 13, 2020, Mar 12, 2021, Jul 9, 2021, Nov 12, 2021

Interactive Data Visualization

This course will teach you the principles of the visual display of data both for presentation and analysis data.

Topic: Analytics, Data Exploration | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 10, 2020, Nov 13, 2020, Mar 12, 2021, Jul 9, 2021, Nov 12, 2021

Introduction to Network Analysis

This course will teach you a mix of quantitative and qualitative methods for describing, measuring, and analyzing social networks.

Topic: Analytics, Data Exploration | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Sep 11, 2020, Jan 8, 2021, Sep 10, 2021

Optimization with Linear Programming

This course will teach you the use of mathematical models for managerial decision making and covers how to formulate linear programming models where multiple decisions need to be made while satisfying a number of conditions or constraints.

Topic: Data Science, Operations Research | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 17, 2020

Predictive Analytics 1 – Machine Learning Tools

This online course introduces the basic paradigm of predictive modeling: classification and prediction.

Topic: Analytics, Prediction/Forecasting | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020, Jan 15, 2021

Predictive Analytics 2 – Neural Nets and Regression

As a continuation of Predictive Analytics 1, this course introduces to the basic concepts in predictive analytics to visualize and explore predictive modeling.

Topic: Analytics, Prediction/Forecasting | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 10, 2020, Nov 13, 2020

Predictive Analytics 3 – Dimension Reduction, Clustering, and Association Rules

This course will teach you key unsupervised learning techniques of association rules – principal components analysis, and clustering – and will include an integration of supervised and unsupervised learning techniques.

Topic: Analytics, Prediction/Forecasting | Skill: Introductory, Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: May 15, 2020, Sep 11, 2020

Risk Simulation and Queuing

This course will teach you modeling technique making decisions in the presence of risk or uncertainty, including risk analysis using Monte Carlo simulation, queuing theory for problems involving waiting lines, and decision trees for analyzing problems with multiple discrete decision alternatives.

Topic: Analytics, Operations Research | Skill: Introductory | Credit Options: ACE, CAP, CEU
Class Start Dates: May 1, 2020, Nov 13, 2020

Elective Courses

In addition to the required courses for the Programming for Data Science Certificate Program, you must choose two electives from the list below to complete your program:

Spatial Statistics for GIS Using R

This course will teach you spatial statistical analysis methods to address problems in which spatial location. This course will explain and give examples of the analysis that can be conducted in a geographic information system such as ArcGIS or Mapinfo.

Topic: Statistics, Analytics, Data Exploration, Statistical Modeling, Using R | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jun 5, 2020, Oct 23, 2020

Survival Analysis

This course will teach you the various methods used for modeling and evaluating survival data or time-to event data.

Topic: Statistics, Biostatistics, Statistical Modeling | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Sep 18, 2020, Mar 5, 2021, Sep 17, 2021

Persuasion Analytics and Targeting

This course will teach you how to apply predictive modeling methods to identify persuadable individuals and to target voters in political campaigns.

Topic: Analytics, Prediction/Forecasting | Skill: Intermediate | Credit Options: ACE, CEU
Class Start Dates: Aug 21, 2020

Logistic Regression

This course will teach you logistic regression ordinary least squares (OLS) methods to model data with binary outcomes rather than directly estimating the value of the outcome, logistic regression allows you to estimate the probability of a success or failure.

Topic: Statistics, Statistical Modeling | Skill: Intermediate | Credit Options: CAP, CEU
Class Start Dates: Jul 17, 2020

Machine Learning with Weka

This course focuses is on learning the Weka tool in contrast to other courses where the focus is on a more detailed study of the data mining methods.

Topic: Data Science, Machine Learning | Skill: Intermediate | Credit Options: CEU
Class Start Dates: Feb 12, 2021

Matrix Algebra

This course will teach you the basics of vector and matrix algebra and operations necessary to understand multivariate statistical methods, including the notions of the matrix inverse, generalized inverse and eigenvalues and eigenvectors.

Topic: Statistics, Statistical Modeling | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Aug 14, 2020

Natural Language Processing

This course will teach you the algorithms, techniques and software used in natural language processing (NLP).

Topic: Data Science, Machine Learning, Text Mining | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Jul 10, 2020

Cluster Analysis

This course will teach you how to use various cluster analysis methods to identify possible clusters in multivariate data. Methods discussed include hierarchical clustering, k-means clustering, two-step clustering, and normal mixture models for continuous variables.

Topic: Statistics, Analytics, Marketing Analytics, Statistical Modeling | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: May 29, 2020

Discrete Choice Modeling and Conjoint Analysis

This course will teach you to design appropriate conjoint and choice studies using surveys, panels, designed experiments, be able to analyze and interpret the resulting data.

Topic: Analytics, Marketing Analytics | Skill: Intermediate, Advanced | Credit Options: CAP, CEU
Class Start Dates: Aug 28, 2020

Financial Risk Modeling

This course will teach you how to model financial events that have uncertainties associated with financial events.

Topic: Analytics, Operations Research | Skill: Intermediate, Advanced | Credit Options: ACE, CAP, CEU
Class Start Dates: Jun 12, 2020

Integer and Nonlinear Programming and Network Flow

This course will teach you a number of advanced topics in optimization: how to formulate and solve network flow problems; how to model and solve optimization problems; how to deal with multiple objectives in optimization problems, and techniques for handling optimization problems.

Topic: Analytics, Operations Research | Skill: Intermediate | Credit Options: ACE, CAP, CEU
Class Start Dates: Sep 25, 2020, Sep 24, 2021

Course Calendar

You can get started with any of these courses:

Predictive Analytics 1
Forecasting Analytics
Interactive Data Visualization
Optimization – Linear Programming

Try it out: take one of the courses, then apply it retroactively to your certificate program after you enroll.

Risk Simulation and Queuing	(4-week class)	May 1, 2020
Predictive Analytics 1 - Machine Learning Tools	(4-week class)	May 15, 2020
Predictive Analytics 3 - Dimension Reduction, Clustering, and Association Rules	(4-week class)	May 15, 2020
Forecasting Analytics	(4-week class)	Jul 10, 2020
Interactive Data Visualization	(4-week class)	Jul 10, 2020
Predictive Analytics 2 - Neural Nets and Regression	(4-week class)	Jul 10, 2020
Optimization with Linear Programming	(4-week class)	Jul 17, 2020
Introduction to Network Analysis	(4-week class)	Sep 11, 2020
Predictive Analytics 1 - Machine Learning Tools	(4-week class)	Sep 11, 2020
Predictive Analytics 3 - Dimension Reduction, Clustering, and Association Rules	(4-week class)	Sep 11, 2020

What Our Students Say

This course will help me handle statistical analyses and related consultancy in a correct, professional, and intelligent way.

Alfred Keter

Senior Data Analyst at National AIDS and STI Control Program (NASCOP)

I enjoyed the course thoroughly. The question-answer sessions (discussions) were really helpful in understanding the concept. I have definitely gained a lot of knowledge about microarray analysis.

Pooja Nashikkar

Chaitanya Software Technologies

Tuition and Fees

Our Analytics for Data Science Certificate program – the approximate equivalent of a Mastery Degree – is a fraction of the cost of what you would pay at a university. The workload is equal to roughly 28 credits in the U. S. academic system which are transferable via the American Council on Education. Choose to pay as you go, or get a discount for paying in full today.

Pay As You Go

$5,743

Pay In Advance

$5,000

Frequently Asked Questions

Are there admission requirements?

You should have recently had introductory statistics, equivalent to our Statistics 1 and Statistics 2 courses. If you haven’t, or if you’d like to go over that basic material again as a refresher course, we’ll put enroll in Statistics 1 and Statistics 2 at no charge once we accept your application.

Please see our knowledge center for more information.

Are courses eligible for CEU?

Many of the courses at The Institute for Statistics Education have been recommended for C.E.U.’s, based on the length of the course (typically 5.0 CEUs for 4-week courses).

Are Statistics.com courses certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information, go to www.schev.edu

Are courses eligible for college credit?

Many of the courses at The Institute for Statistics Education have been recommended for academic credit by The American Council on Education (ACE). ACE-accredited courses can be transferred to another educational institution that accepts ACE credit.

Are the certificate programs accredited?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV).

In addition, many of the courses at The Institute for Statistics Education have been recommended for credit by The American Council on Education (ACE), INFORMS, and can be used as CEUs in many programs.

The American Council on Education (ACE) approved credit for many of the required courses for our certificate programs and can be transferred to another educational institution that accepts ACE credit.

Visit our knowledge base and learn more.

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Additional Series Information

Organization of Program

The courses in this certificate program are all standard Statistics.com courses – small classes, regular interaction with your instructor throughout the course, rapid expert feedback on your homework and projects. You can register for the courses individually, and even incorporate courses that you have recently successfully completed.

Time Requirements

There are 10 courses, each are 4 weeks long. You may build your own course calendar to meet your individual requirements. The certificate program can be completed in less than a year or two, depending on your time constraints and course availability.

Course Fee & Information

The fee for the Analytics for Data Science Certificate program if you pay in full is only $5,000. This includes the program registration fee, and individual course fees. It reflects considerable savings that are available if you pay the program cost upon enrollment. Note: all tuition held on account must be used within two (2) years from date of purchase.

You also have the option to pay on a course-by-course basis with our pay-as-you-go model estimated fee of $5,782. You will need to pay the registration fee to enroll which is $495. The “pay-as-you-go” estimate includes the registration fee, individual course fees (required: $3,872 and estimated electives: $915) that you pay as you progress through the program, as well as various tuition savings available to you once you are a matriculated certificate candidate at the Institute. The actual total cost of the program may vary slightly depending on several factors and may differ slightly from the estimate above; fees are subject to change without prior notice.

Options for Credit and Recognition

Our Analytics for Data Science Certificate program – the approximate equivalent of a Masters Degree – is roughly equal to 28 credits in the U. S. academic system, which are transferable via the American Council on Education credit recommendation service. More details on ACE and accreditation can be found here.

Miscellaneous

Visit our Knowledge Base to learn more about our certificate programs.