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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study, Virtual Classroom	Video and Text Based

Course Overview

Individuals with a hybrid combination of analytical abilities and domain-specific experience are required to accelerate data-driven business choices as the amount of data available affects the way businesses function. The Data Analysis and Visualization online course by Rice University equips participants with the information and skills they need to analyze, display, and convey data insights successfully within their company.

According to the Entrepreneur report, Businesses that use big data analytics can save 10% on their overall costs. The Data Analysis and Visualization Training teaches how to use technology resources like SQL, Tableau, and VBA with the help of industry professionals. The program also teaches how to use sophisticated Excel tools, databases, and realistic statistics to grasp the basics of statistical analysis.

A Businesswire study says that by 2022, business analytics and big data are expected to generate $274.3 billion in global revenue. Data Analysis and Visualization certification course teaches how to communicate successfully with clients through data narration, using data-driven conclusions and excellent visualization approaches.

The Highlights

Online learning
Projects and assessments
8 weeks duration
Course provider Getsmarter
Self-paced learning
Split option of payment
7-10 hours per week
Rice University offering
Shareable certificate
Downloadable resources

Programme Offerings

Infographics
Live polls
Case Studies
Offline resources
video lectures
Self-paced learning
online learning
quizzes

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Susanne M Glasscock School of Continuing Studies, Houston

The Data Analysis and Visualization certification fee are Rs. 150,076 (Incl of all taxes). Participants can pay the program fee in full at the time of enrolling or choose the split option for paying the whole fee in two payments of Rs.76,025 each. If the applicant opts for the split payment option, they will be charged an additional 3% administration fee. Payments can be made by credit/debit card, bank wire transfer, or electronic fund transfer/bank wire transfer.

Data Analysis and Visualization Fee Structure

Fee type	Fee amount in INR
Data Analysis and Visualization fees	Rs. 150,076

Eligibility Criteria

Certification Qualifying Details

To qualify for the Data Analysis and Visualization certification by Get Smarter, the candidates must complete the online program modules as well as present projects and assignments. Students will have to participate in the live polls, quizzes surveys, case studies, and other formative tasks in the classroom. To qualify for certification, students must complete a series of online projects and assignments and meet all of the requirements outlined in the course manual.

What you will learn

Analytical skillsKnowledge of Data Visualization

After completing the Data Analysis and Visualization certification course, Candidates will develop the capacity to properly display data using the foundations of data analysis and the ability to use narrative to explain the outcomes of your data analysis to corporate stakeholders. Learners will gain working knowledge of advanced and in-demand technologies like SQL, Tableau, and VBA along with the abilities required to find solutions for automating data analysis tasks.

Who it is for

Data AnalystData Administrator

Data analysts who deal with analytical and data models to make informed business decisions and perform specific functions in an organisation.
Those in management positions, i.e, managers who want to use data to influence operational and strategic choices, and who want to learn how to do so with the help of the right tools.
Data administrators who are interested in moving into an analytical capacity and becoming acquainted with data visualization and analysis.

Admission Details

To get admission to the Data Analysis and Visualization classes, follow the steps mentioned below:

Step 1. Visit the official course page on Getsmarter by following the given link

(https://www.getsmarter.com/products/rice-data-analysis-and-visualization-online-short-course)

Step 2. To start the registration process, click the ‘Register Now’ button

Step 3. Read and agree with the provider terms to continue

Step 4. Create a profile on the Getsmarter portal by providing personal details

Step 5. Fill in the optional fee sponsor information and provide the billing address details

Step 6. Pay the fee amount and start learning online

The Syllabus

Discuss common data cleaning objectives
Recall the basic functionality of Excel, and recognize formula syntax and where to find function documentation
Recognize the limitations of visualization types
Calculate optimal solutions using the solver tool in Excel
Discuss best practices for visualization selection
Create a range of possibilities using data tables in Excel

Discuss the limitations of a hypothesis
Define elements of a testable hypothesis
Identify different sources for data retrieval
Articulate conclusions are drawn from an experiment
Discuss a proposed experiment
Critique the limitations of an analysis

Execute basic database operations
Identify the need for databases in analytics
Identify the need for normalization and data retrieval using joins
Discus processes in a data retrieval strategy
Design SQL tables
Design a query to retrieve data from a SQL database and import it to a CSV file

Calculate measures of centrality and variability to summarize a data set and describe its spread
Use common descriptive statistics to describe numerical data
Calculate the probability of an event, given information about a sample
Identify common statistical misconceptions and pitfalls of interpretation
Analyze the results of a statistical test and identify the level of confidence in the results
Discuss issues around statistical analysis

Identify the appropriate regression model to use based on the distribution of data
Calculate linear and logistic regression models given a numerical data set
Calculate confidence intervals of future values
Discuss the strengths and weaknesses of different models
Interpret forecasts based on a predictive model
Identify common limitations and pitfalls of forecasts

Identify common mistakes when plotting data
Describe important considerations when communicating analyses to a non-technical audience
Review common ethical issues in data analysis
Discuss modern regulations around data and analysis
Discuss the considerations of an ethically ambiguous situation
Evaluate the guidelines for communication, ethics, and regulations within your organization