COURSE OVERVIEW
GE0039 : Data Analysis
![Data Analysis](/storage/publiccourse/files/Qbyy1KXYj9B3i65VzPiRY0vod9HeyOThWMPHQfx5.bmp)
OVERVIEW
COURSE TITLE | : | GE0039 : Data Analysis |
COURSE DATE | : | Nov 03 - Nov 07 2024 |
DURATION | : | 5 Days |
INSTRUCTOR | : | Dr. John Petrus |
VENUE | : | Muscat, Oman |
COURSE FEE | : | $ 5500 |
Register For Course Outline |
OTHER SCHEDULED DATES
Date | : | Aug 11 - Aug 15 (5 Days) | Location | : | Dubai, UAE | Classroom Fee (US$) | : | $ 5500 | Course Info |
Course Description
This course is designed to provide participants with a detailed and up-to-date overview of Data Analysis. It covers the role of data in operations and production; the data collection techniques, central tendency and variability; visualizing data using histograms, boxplots and scatterplots; the importance of data cleaning, handling missing values and detecting and managing outliers; the right tool for the task using Excel, R, Python and other analytical tools; the relationship of correlation and causation between variables; and the simple linear regression and multiple regression.
During this interactive course, participants will learn the time series analysis, quality control and statistical process control (SPC) and experimental designing and analysis of variance (ANOVA); the non-parametric statistics and inventory management analysis and supply chain analytics; the demand forecasting, optimization techniques and Lean and Six Sigma analytics; the KPIs for operational excellence and operational metrics for decision making; the machine learning basics and predictive maintenance, production scheduling with data, risk management and scenario analysis; the operational and production reporting and data driven decision making; the advanced topics like Big Data and IoT in production; and the future trends in data analysis for production.
link to course overview PDF
During this interactive course, participants will learn the time series analysis, quality control and statistical process control (SPC) and experimental designing and analysis of variance (ANOVA); the non-parametric statistics and inventory management analysis and supply chain analytics; the demand forecasting, optimization techniques and Lean and Six Sigma analytics; the KPIs for operational excellence and operational metrics for decision making; the machine learning basics and predictive maintenance, production scheduling with data, risk management and scenario analysis; the operational and production reporting and data driven decision making; the advanced topics like Big Data and IoT in production; and the future trends in data analysis for production.
TRAINING METHODOLOGY
This interactive training course includes the following training methodologies as a percentage of the total tuition hours
LecturesWorkshops & Work Presentations
Case Studies & Practical Exercises
Videos, Software & Simulators
In an unlikely event, the course instructor may modify the above training methodology before or during the course for technical reasons.
VIRTUAL TRAINING (IF APPLICABLE)
If this course is delivered online as a Virtual Training, the following limitations will be applicable
Certificates | : | Only soft copy certificates will be issued to participants through Haward’s Portal. This includes Wallet Card Certificates if applicable |
Training Materials | : | Only soft copy Training Materials (PDF format) will be issued to participant through the Virtual Training Platform |
Training Methodology | : | 80% of the program will be theory and 20% will be practical sessions, exercises, case studies, simulators or videos |
Training Program | : | The training will be for 4 hours per day starting at 09:30 and ending at 13:30 |
H-STK Smart Training Kit | : | Not Applicable |
Hands-on Practical Workshops | : | Not Applicable |
Site Visit | : | Not Applicable |
Simulators | : | Only software simulators will be used in the virtual courses. Hardware simulators are not applicable and will not be used in Virtual Training |
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