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Certificates: E-Commerce" certificate
Certificate "Statistics and data analysis"
Data Analytics" certificate -
Examination: Praxisbezogene Projektarbeiten mit Abschlusspräsentationen
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Teaching Times: Full-timeMonday to Friday from 8:30 a.m. to 3:35 p.m. (in weeks with public holidays from 8:30 a.m. to 5:10 p.m.)
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Language of Instruction: German
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Duration: 12 Weeks
E-Commerce
Basics of e-commerce (approx. 2 days)
Introduction to e-commerce and digital commerce
Business models and framework conditions
Players and enablers in e-commerce
Online sales channels and multi-channel strategies
Legal aspects (approx. 2 days)
Legal principles in online trading
Imprint, general terms and conditions and right of withdrawal
Data protection and DSGVO
International B2C online trade
EU product safety regulation: General Product Safety Regulation (GPSR)
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Online store systems and design (approx. 3 days)
Store systems and comparison of providers
Functionalities and design
Usability and user experience (UX)
Product presentations and descriptions
Checkout process optimization
Online marketing and customer acquisition (approx. 3 days)
Search engine marketing (SEA) and optimization (SEO)
Social media marketing and content strategies
Email marketing and newsletter optimization
Affiliate marketing and influencer cooperations
Display advertising and retargeting
Payment systems and finance (approx. 2 days)
Payment methods and providers in e-commerce
Risk management and fraud prevention
Debt collection and receivables management
Controlling and key figures in online retail
Logistics and fulfillment (approx. 2 days)
E-commerce logistics and shipping options
Warehouse and merchandise management systems
Returns management and optimization
International logistics and customs clearance
Customer service and CRM (approx. 2 days)
Customer service strategies in e-commerce
CRM systems and customer loyalty measures
Complaint management and conflict resolution
After-sales service and customer feedback
Web controlling and data analysis (approx. 2 days)
Web analytics tools and their use
Conversion optimization and A/B testing
Data analysis and interpretation
KPI tracking and reporting
Project work (approx. 2 days)
Conception and implementation of an e-commerce project
Presentation of the project result
Statistics and data analysis
Statistical basics (approx. 6 days)
Measurement theory basics (population, sample, sample types, measurement, scale levels)
Univariate descriptive statistics (frequency distributions, central measures, measures of dispersion, standardization, histograms, bar charts, pie charts, line charts, box plots)
Bivariate descriptive statistics (measures of correlation, correlation coefficients, crosstabs, scatter plots, grouped bar charts)
Basics of inductive inferential statistics (probability distributions, normal distribution, sampling distribution of the mean, significance test, null hypothesis test, significance level, effect size, parameter estimation, confidence intervals, error bar charts, power analysis, sample size)
Data preparation and data cleansing with suitable software
Descriptive analysis
Visualization of statistical results
AI-supported analysis and interpretation of statistical results
Methods for comparing two groups (approx. 5 days)
z-test, t-test for one sample
t-test for independent and related samples
Pretest-posttest designs with two groups
Supporting significance tests (Anderson-Darling test, Ryan-Joiner test, Levene test, Bonett test, significance test for correlations)
Nonparametric methods (Wilcoxon test, sign test, Mann-Whitney test)
Contingency analyses (binomial test, Fisher's exact test, chi-square test, cross-tabulations, measures of association)
Interpretation of test results
AI-supported interpretation of results
Basics of regression analysis (approx. 2 days)
Linear regression
Model interpretation
AI-supported model interpretation
Correlation analysis
Methods for comparing the means of several groups (approx. 3 days)
One-factorial and two-factorial analysis of variance (ANOVA)
Post-hoc analyses
Interpretation of group differences
Multi-factorial analysis of variance (general linear model)
Fixed, random, crossed and nested factors
Multiple comparison methods (Tukey-HSD, Dunnett, Games-Howell)
Interaction analysis
Power analysis for variance analyses
Introduction to Design of Experiments (DoE) (approx. 1 day)
Full factorial and partial factorial experimental designs
Project work (approx. 3 days)
To consolidate the content learned
Presentation of the project results
Data analytics
Introduction to data analysis (approx. 1 day)
CRISP-DM reference model
Data analytics workflows
Definition of artificial intelligence, machine learning, deep learning
Requirements and role in the company of data engineers, data scientists and data analysts
Review of Python basics (approx. 1 day)
data types
Functions
Data analysis (approx. 3 days)
Central Python modules in the context of data analytics (NumPy, Pandas)
Process of data preparation
Data mining algorithms in Python
Artificial intelligence (AI) in the work process
Presentation of specific AI technologies
and possible applications in the professional environment
Data visualization (approx. 3 days)
Explorative data analysis
insights
Data quality
Benefit analysis
Visualization with Python: Matplotlib, Seaborn, Plotly Express
Data storytelling
Data management (approx. 2 days)
Big data architectures
Relational databases with SQL
Comparison of SQL and NoSQL databases
Business Intelligence
Data protection in the context of data analysis
Data analysis in a big data context (approx. 1 day)
MapReduce approach
Spark
NoSQL
Dashboards (approx. 3 days)
Library: Dash
Structure and customizing of dashboards
callbacks
Text Mining (approx. 1 day)
Data preprocessing, visualization
Library: SpaCy
Project work (approx. 5 days)
To consolidate the content learned
Presentation of the project results
Changes are possible, the course content is updated regularly.
After completing this course, you will have a sound understanding of all the important aspects of online retail. You will be familiar with the legal principles, have mastered the selection and design of store systems and be able to develop effective online marketing strategies. You will also be familiar with payment systems, logistics, customer service and data analysis. With this knowledge, you will be able to successfully set up, operate and continuously optimize an online store.
You will also understand the basics of statistics, be able to process and evaluate data and present, explain and interpret statistical data analyses and results using graphics.
Furthermore, you can analyse, visualize and manage data. You also understand the use of dashboards and text mining.
This course is aimed at people who are responsible for the conception, design and practical implementation of websites with e-commerce functions and who wish to acquire the necessary knowledge and skills.
After completing the course, you will have acquired a broad basic knowledge that will enable you to enter various fields of activity in online retail. The course is aimed at people who want to actively participate in the conception, design and implementation of e-commerce projects.
As companies also have to manage and structure ever-increasing volumes of data in order to evaluate and target their business processes, data analysis skills are in demand in all sectors.
Your meaningful certificate provides a detailed insight into the qualifications you have acquired and improves your career prospects.
Didactic concept
Your lecturers are highly qualified both professionally and didactically and will teach you from the first to the last day (no self-study system).
You will learn in effective small groups. The courses usually consist of 6 to 25 participants. The general lessons are supplemented by numerous practical exercises in all course modules. The practice phase is an important part of the course, as it is during this time that you process what you have just learned and gain confidence and routine in its application. The final section of the course involves a project, a case study or a final exam.
Virtual classroom alfaview®
Lessons take place using modern alfaview® video technology - either from the comfort of your own home or at our premises at Bildungszentrum. The entire course can see each other face-to-face via alfaview®, communicate with each other in lip-sync voice quality and work on joint projects. Of course, you can also see and talk to your connected trainers live at any time and you will be taught by your lecturers in real time for the entire duration of the course. The lessons are not e-learning, but real live face-to-face lessons via video technology.
The courses at alfatraining are funded by Agentur für Arbeit and are certified in accordance with the AZAV approval regulation. When submitting a Bildungsgutscheinor Aktivierungs- und Vermittlungsgutschein, the entire course costs are usually covered by your funding body.
Funding is also possible via Europäischen Sozialfonds (ESF), Deutsche Rentenversicherung (DRV) or regional funding programs. As a regular soldier, you have the option of attending further training courses via Berufsförderungsdienst (BFD). Companies can also have their employees qualified via funding from Agentur für Arbeit (Qualifizierungschancengesetz).