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AIT Analytics academy

AIT Analytics academy. Data Analytics Certificate Program. Introducing the Data Analytics Certificate Program. The job outlook is incredible -- now and for the foreseeable future: Why Data Analytics? In a word—jobs!

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AIT Analytics academy

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  1. AIT Analytics academy Data Analytics Certificate Program

  2. Introducing the Data Analytics Certificate Program The job outlook is incredible -- now and for the foreseeable future: • Why Data Analytics? In a word—jobs! • McKinsey: The U.S. alone faces a shortage of 140,000 to 190,000 people with analytical expertise and 1.5 million managers with the skills to understand and make decisions based on the analysis of big data. • According to IBM, the number of jobs for all US data professionals will increase by 364,000 to 2,720,000 by 2020. • There are jobs in marketing, finance, insurance, medicine, engineering, energy, transportation, agriculture, manufacturing…every role in every sector of the economy!

  3. How the Data Analytics Certificate Program Works The Data Analytics Certificate Program is: • 100% project-based, learn by doing • A series of five online, collaboration-driven courses that provide real-world, skills-based training • Taught by live, virtual mentors who coach students, rather than lecturing, and evaluate based on the work produced You will leave the program with end-to-end experience working on nine projects resulting in an impressive portfolio of professional work.

  4. Unique Program Approach • Story-centered curricula: Proven highly effective in skill-building programs, developed with industry pioneers. • Student work is framed in a realistic story of professional practice and the work situation to which they aspire. • Students receive feedback on projects from mentors. • Students reflect on lessons learned from their experiences, then move to the next “scene” in the story, which links to and builds on what they have done.

  5. Unique Program Approach • Faculty mentors enhance the online experience • One-to-one coaching nurtures excellence. • Strong emphasis on job skills beyond the technical • Principled decision making, teamwork, verbal and written communication, negotiation and self-directed learning. • Students build a portfolio of professional-quality work • Deliverables roll up into a portfolio that can be presented to employers.

  6. Course Outline

  7. Module 1: Customer Behavior and Product Profitability You are a member of the Data Analytics team in an electronics company who will use machine learning to provide insight into customer buying trends and preferences. Your tasks are to: • Analyze differences in customer behavior • Predict the profitability of potential new products Tool used: • RapidMiner

  8. Module 2: Predicting Customer Preferences You continue working for the electronics company. Your tasks are to: • Develop predictive models to predict customer product preferences. • Build a recommender system using association rules Tools used: • R, R Studio, R statistics and machine learning packages, SQL

  9. Module 3: Deep Analytics and Visualization You are working for an “Internet of Things” analytics firm. Your tasks are to: • Model smart energy usage • Develop an indoor locationing solution Tools used: • Advanced R packages for data visualization, SQL, time series analysis and machine learning

  10. Module 4: Big Data – Web Mining You are working for a big data consulting firm. • Your client is an app developer that has hired you to conduct a web sentiment analysis of users’ attitudes towards various models of smartphones. Tools used: • Amazon Web Services, Elastic Map Reduce, Hadoop

  11. Module 5: Data Science with Python You are working as a Data Scientist for a third-party credit rating firm. Your tasks are to: • Develop a predictive model to better classify “at-risk” potential customers. • Complete a capstone project of your choice. Tools used: • Python, Jupyter Notebooks, Numpy, Pandas, MatPlotLib, Sci-Kit Learn

  12. Program Requirements • Prerequisites: • One year of work experience (no need to be technical). • High level of computer literacy. • Familiarity with Windows, Mac or Linux operating systems, specifically: • Creating and managing folders within folders. • Creating and extracting files from zip archives. • Elementary administrative tasks (e.g., installing software requiring admin privileges). • Basic familiarity with Microsoft Office or equivalent. • Computer requirements: • Modern laptop or desktop computer with high-speed Internet connection.

  13. Suggested Prep Work Prior to Course Start Date • Take a tour of RapidMiner • Read Section 1 in Data Mining for the Masses, 3rd edition • Work through designated exercises in the RapidMiner Learn tutorials • Additional recommended reading: “Statistics For Absolute Beginners” by O. Theobald

  14. Registration and Start Date • A registration portal will be available shortly online at: http://www.yunuscenter.ait.asia/ • Course dates: • Data Analytics Certificate Program, 18/09/2019

  15. Cost Program Cost

  16. Payment Plan Options • Data Analytics Certificate Program - A 30% deposit is required upon registration. The next month, ½ of the remaining balance is due. The third month, the remaining balance is due.

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