Selasa, Agustus 4Informasi Jadwal / Schedule Training 2020 - 2021
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Training Economic Analysis and Data Analytics

Economic Analysis and Data Analytics Training

Course Overview

The underlying skills of data analysis encompass common patterns across every organisation and industry, but there are also some particular factors when conducting data analysis.

This Economic Analysis and Data Analytics course combines skills in programming, data gathering, and data management with skills in economic reasoning and statistical analysis.

ThisEconomic Analysis and Data Analytics course is intended to bring together participants with concentrated careers that require expertise in creating data systems with analytical and statistical proficiencies.

Course Objectives

Upon completing this Economic Analysis and Data Analytics course successfully, participants will be able to:

  • Apply economic models to business problems
  • Identify contexts and applications of data in specific industries and in organisational settings
  • Implement conventional data analysis techniques and customising them for exceptional circumstances
  • How to utilise different types of data in different scenarios
  • Analyse data with advanced statistical and econometric techniques
  • Learn and employ techniques of data analysis to form business strategies
  • Apply computer programming and computing software to analysis of data
  • Learn how to build a career in economics or data analysis

Who Should Attend?

Professionals in the following fields will benefit from this Economic Analysis and Data Analytics Training Program:

  • Management, Economics, and Consumer Studies
  • International Development Studies
  • Environmental Sciences
  • Professionals who wish to specialise in economics
  • Professionals who wish to specialise in data analytics
  • New MSc Biobased Sciences for students with a specialisation in economics
  • PhD candidates in the field of economics
  • C-level executives who need to understand economic strategies
  • Decision-makers
  • Government employees who form regulations
  • Customer representatives

Course Outline

MODULE 1: THE BASICS

  • Basics of economic analysis
  • Sources of economic data
  • Microeconomic data
  • Macroeconomic data
  • Economic forecasting methods
  • Regression analysis in economics

 

MODULE 2: ECONOMIC CYCLES

  • Trend analysis in forecasting
  • Case study – real estate
  • Coefficients
  • Significance
  • Standard errors
  • Serial correlation in data
  • Analysing results

 

MODULE 3: FORECASTING ECONOMIC TRENDS

  • Fixed effects regressions
  • Omitted variables bias
  • Binary outcome
  • Binary regressions
  • Logit models
  • Probit models
  • Advanced regression applications
  • Federal Reserve Economic Database (FRED)
  • Difference-in-differences analysis
  • Difference-in-differences estimator

 

MODULE 4: USE ECONOMIC FORECASTS

  • Understanding economic output
  • Long-term capital gains rate
  • Forecast accuracy
  • Scenario analysis
  • Using macro and microeconomic data in forecasts

 

MODULE 5: MICROECONOMIC ANALYSIS

  • Understanding microeconomic analysis
  • Corporate strategic decisions
  • Market and industrial organisation
  • Game theory
  • Econometrics

 

MODULE 6: CORPORATE FINANCE

  • Understanding the role of corporate finance in economic analysis
  • Analysis of a firm’s financial decisions
  • Use of financial models in economics
  • Quantitative case studies

 

MODULE 7: DATA ANALYTICS

  • Data Analysis in Context
  • Data Analysis for Business
  • Data Analysis for Education
  • Data Analysis for Healthcare
  • Data Analysis for Government

 

MODULE 8: FORECASTING METHODS

  • Forecasting demand and regression
  • Causal methods
  • Time-series methods
  • Qualitative methods
  • Predicting values with regressions

 

MODULE 9: DATA AND ANALYSIS IN THE REAL WORLD

  • Thinking about Analytical Problems
  • Conceptual Business Models
  • The information-Action Value Chain
  • The information-Action Value Chain
  • Real-World Events and Characteristics
  • Data Capture by Source Systems

 

MODULE 10: ANALYTICAL TOOLS

  • Data Storage and Databases
  • Big Data & the Cloud
  • Virtualisation, Federation, and In-Memory Computing
  • The Relational Database
  • Data Tools Landscape
  • The Tools of the Data Analyst

 

MODULE 11: PERFORM PREDICTIVE ANALYTICS TASKS

  • Cross-Validation and Confusion Matrix
  • Assessing Predictive Accuracy Using Cross-Validation
  • Building Logistic Regression Models using XLMiner
  • How to Build a Model using XLMiner

 

MODULE 12: DECISION ANALYTICS

  • Business Problems with Yes/No Decisions
  • Formulation and Solution of Binary Optimisation Problems
  • Metaheuristic Optimisation
  • Chance Constraints and Value at Risk
  • Simulation Optimization

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General Notes

  • All our courses can be facilitated as Customized In-House Training course.
  • Course duration is flexible and the contents can be modified to fit any number of days.
  • As for Open Enrolment Courses, we offer our clients the flexibility to chose the location, date, and time and our team of experts who are spread around the globe will assist in facilitating the course.
  • The course fee includes facilitation, training materials, 2 coffee breaks, buffet lunch and a Certificate of successful completion of Training.
  • FREE Consultation and Coaching provided during and after the course.

VENUE 

Yogyakarta, Jakarta, Bandung, Bogor, Cirebon, Solo, Semarang, Surabaya, Malang, Bali, Lombok, Samarinda, Balikpapan, Banjarmasin, Pontianak, Makassar, Medan, Palembang, Lampung, dll serta Timor Leste, Thailand, Singapore , Kuala Lumpur.  (dengan harga dan minimal kuota yang berbeda)

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