Good data selection and/or collection are the foundation for effective data analysis. This demands a thorough understanding of all data kinds and the various sources that they come from. Additionally, by arranging it correctly, all of the data may be easily shown under various charts, and they can all be described using appropriate and effective descriptive statistics measures.
The foundational concepts of this course include developing a clever data collection procedure, choosing the optimum sampling strategy, confirming the accuracy of the data stored for analysis, and comprehending all the choices for visualization and the related descriptive statistical KPIs. Prior to beginning any work or even a career in the realm of data, this course addresses all approaches and instruments for thorough data analysis. The course also acts as a prerequisite for any course or program in machine learning.
Additionally, this course aims to give participants a clear and comprehensive understanding of data structuring for effective data analysis, scientific group profiling through intelligent and effective data analysis, and appropriate data manipulation using a variety of tools currently available on the market.
Understand and organize the phases of a successful data analysis project.
Convert any industry into a thorough database.
Analyze and assess the quality of the data.
Basic data interpretation and description using full descriptive statistics
Discover the full history of data analysis.
All practitioners of machine learning and artificial intelligence (AI) start with applied data analysis. It is fundamental information that applies to all fields and data-related jobs.
The different types of Data
Data sources
Data
Variables
Data visualization
Pies, Doughnuts, Bars
Histograms, Lines, Scatter plots
Heat maps and Tuckey boxes
Geographical maps
Central tendency measurements
Average
Median
Mode
Scatter tendency measurements
Quartile
Variance
Standard deviation
Estimations
Punctual
Confidence Interval
Two men test
Equal variances (t-test)
Unequal variances (t-test – Welch correction)
Two variance tests (F-Test)
Two proportion test (Chi-Square test)
Two distribution tests (Chi-Square test)
Attraction – Repulsion Matrix
Vertical and horizontal profiling
Multiple mean tests
Equal variances (F-Test and ANOVA Table)
Unequal variances (F-Test – Welch Correction)
Multiple Variance test
Levene test
Chi-Square test
Multiple proportion test (Chi-Square test)
Multiple distribution test (Chi-Square test)
Attraction – Repulsion Matrix
Vertical and horizontal profiling
Mean pair comparisons methods:
General
Bonferroni
Tukey - Kramer
Simple linear regression
Line equation
Testing the regression line validity (t-nullity test)
R vs. R Square interpretation
ANOVA table analysis
Simple logistic regression
Probabilistic model
Testing the model validity (Chi-Square test)
Predicting classification
Odds ratio interpretation
Data analysis project best practices
Ask
Design
Preview
Analyze
Communicate
Sampling methods
Random and systematic
Multilevel, stratified, and cluster
Convenient, quota, and judgmental
PMP for research projects overview
Integration, cost, scope, time, cost, quality, communication
Social media marketing is one of the most important digital marketing channels. Social media marketing uses social media platforms to create awareness about the product. Digital Marketing uses online and offline channels to promote products to the customer.
We all operate in an increasingly complex commercial and professional environment that requires us to negotiate on a daily basis not only with customers, clients, suppliers and contractors but also with managers, fellow employees, and colleagues within our own organization.
The key to any successful operation lies in the effective management of risks; the ability to seize opportunities, minimize threats, and optimize results. However, risk management is too often treated as a reactive process, or worse, not done at all. In this Operations Risk Management and Mitigation training course, you’ll work through the proactive approach to both sides of risk: threats and opportunities. The approach applies a proven six-step methodology of risk planning through identification, analysis, and control.
Maintaining a high level of productivity in today's successful businesses takes work and continuous learning in a variety of management skills and techniques. To be successful in daily work tasks, knowledge, and skills in management techniques must be learned, practiced, and implemented. People in all types of organizations find themselves needing to find more productive methods of planning work and tasks, setting appropriate goals, using good interpersonal skills, and using effective means of making decisions. A focus on using productive practices allows for effective and efficient management of work and making changes in the organization.
The ASME Plant Inspector Level 1 training course provides the fundamental principles of the inspection, assessment, and management of fixed pressure equipment. The content of the course is delivered in a systematic manner, from the inspection planning process to inspection practices and evaluation of the associated equipment. It is aimed at the upstream and downstream Petrochemical industry but is equally relevant to stakeholders from other sectors that utilize pressure equipment.
This intensive course covers the in-service inspection methodologies and requirements for piping, pressure vessels, and above ground storage tanks.