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Big Data and Data Analytics Certificate

Currently, demand for workers with analytical expertise is extremely high – join us to obtain a comprehensive introduction into the critical and practical elements of big data analytics, including: data structure, warehousing, statistics, analysis, patterns, trends, relevancy, model building, visualization techniques and more. Completion of this course can enable students to participate in big data projects as analysts. The course is best suited for individuals and college graduates interested in data-related careers, including positions as business or data analysts. Recommended: degree in or equivalent practical experience in business, science, engineering, software and/or data processing. 

This course provides a comprehensive foundation in big data analytics and covers the important and practical elements of the field. Armed with this training, graduates of the course can participate in big data projects as associate data analysts. 

Join us for 10 full-day sessions spread over ten Saturdays to gain a comprehensive understanding of the critical and practical elements of big data analytics. Offered in an applied format, the program includes practice and lab components to address the applications of Big Data in real world situations. Data-related topics include: structure, warehousing, engineering, mining, pattern recognition, trends analysis, relevancy, modeling, predictive and descriptive analytics, visualization techniques and more.

The course also covers the use of Spark Databricks as a distributed computing framework. Successful completion of this highly intensive course can enable students to participate in big data projects as analysts. The course is best suited for individuals and college graduates interested in big data and related analytics careers, managers considering big data projects, and/or individuals who want to advance their business career.

Program Objectives

Upon successful completion of this intensive program, participants will be able to:

  • Explain big data analytics, and its role in the datafication trend
  • Explain the fundamentals of data engineering
  • Collect, clean, and explore data (perform data wrangling with Azure and Python)
  • Demonstrate the use of data mining techniques
  • Build, train, evaluate, optimize and deploy descriptive and predictive analytics models
  • Demonstrate effective communication skills through data visualization, presentation, and storytelling using Tableau
  • Perform text mining
  • Perform artificial intelligence-based image recognition (deep learning) using NVDIA
  • Use analytics tools including Azure, Python and Tableau for big data analytics projects
  • Leverage Azure Databricks and Spark for scalable machine learning

Upcoming Info Sessions

Prerequisites

Students interested in this program should first complete ECE's Business Intelligence program or have already earned a degree or have equivalent practical experience in any of the following fields: business, banking and finance, supply chain, healthcare, pharma, science, engineering, software, IT, and/or analytics

Technology Requirements

Students are required to possess intermediate-level Excel knowledge including an understanding of workbooks, data entry, formatting, sorting/filtering, formulas, and charts.

Unsure as to the level of your Excel knowledge? Email harjman@emory.edu to request an assessment test or enroll in one of our Microsoft Excel Level 2: Excelling at Excel class options -- plus get a 10% Excel course discount with promo code BUSINTELL

About Big Data

Big Data refers to a huge number of diverse, structured and unstructured data created at high rate. Data sources include sensor networks, social networks, medical records, Internet text and documents, genomics, etc. Big Data can be leveraged to identify issues and opportunities not possible via traditional tools and techniques; a variety of industries currently utilize Big Data, including healthcare, retail, manufacturing, finance and government.

As such, the potential for career enhancement is significant -- according to a report published by McKinsey, "The United States alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers and analysts with the skills to understand and make decisions based on the analysis of big data."

Our courses will prepare you to be a successful professional with a promising career in Big Data analytics. Students who complete our Big Data program will be candidates for our advanced-level courses – including Applied Machine Learning and Data Science with Python, Artificial Intelligence (AI) & Deep Learning. More advanced-level courses – including Data Engineering, Cloud Computing and Internet of Things (IOT) are in progress and will be available soon.

Who is it for?

This course is intended and best suited for the following prospective participants:

  • Individuals and college graduates interested in a big data career as data scientist who have already earned a degree in or equivalent practical experience in business, science, engineering, software and data processing
  • Business intelligence professionals and data analysts who are interested in becoming knowledgeable about Big Data Analytics
  • Business leaders who are contemplating the applicability and utility of big data analytics in their businesses
  • Managers and executives who are interested in becoming effective participants in the selection, implementation and competent use of big data analytic solutions in their businesses

Careers

Big data applications are commonplace -- most large companies have one or more of these applications, providing fast access to large stores of customer and sales data. As the IT organization grows to install, support and maintain these applications, new job categories and new tasks are added to the mix. These may include:

  • big data hardware and software support;
  • business analysts (using analytics to probe and explore the data); and
  • managers who must supervise and prioritize job tasks.

The hardware/software support positions often center on the technical nature of Big Data. The emphasis of our program focuses on the analysts’ and managers’ roles regarding business management of big data.

The following links provide example salaries of Big Data professionals. Please note: these numbers do not reflect entry level salaries; however, the articles may offer relative comparisons.

Big Data Salary

Business Analytics Salary in Atlanta

Program Topics

  1. Introduction to big data analytics
  2. Azure in data analytics
  3. Introduction to Python, Numpy, and Pandas
  4. Data mining
  5. Data engineering
  6. Data wrangling with Azure and Python
  7. Descriptive analytics with Azure and Python
  8. Predictive analytics with Azure and Python
  9. Text mining
  10. Text mining with Azure and Python
  11. Image recognition (deep learning) with NVIDIA
  12. Introduction to Azure Data bricks and Spark
  13. Data visualization and data storytelling with Tableau
  14. Guest Lectures from data analytics experts and leaders in the industry
  15. Practicum and capstone (build, train, and evaluate analytics models)

Payment Options

The easiest way to pay for courses with Emory Continuing Education is using any major credit card including Visa, MasterCard, American Express, or Discover.

VIEW PAYMENT OPTIONS

Deposit Option

Students are able to put down a $500 deposit to secure a spot in this course. The deadline for paying the remaining balance of $3,495 is 10 days prior to the class start date.