facebook
favorite button
super instructor icon
Trusted teacher
This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
member since icon
Since February 2025
Instructor since February 2025
I specialize in tutoring Power BI. My goal is to keep students challenged, but not overwhelmed. I assign homework after every lesson and pro
course price icon
From 13 € /h
arrow icon
I specialize in tutoring Power BI. My goal is to keep students challenged, but not overwhelmed. I assign homework after every lesson and provide periodic progress reports.

I specialize in tutoring Power BI. My goal is to keep students challenged, but not overwhelmed. I assign homework after every lesson and provide periodic progress reports.
Extra information
Bring your own laptop
Location
green drop pin icon
|
Use Ctrl + wheel to zoom!
zoom in iconzoom out icon
location type icon
At student's location :
  • Around Paris, France
Age
Adults (18-64 years old)
Student level
Beginner
Intermediate
Advanced
Duration
30 minutes
60 minutes
The class is taught in
English
Skills
Availability of a typical week
(GMT -05:00)
New York
at home icon
At student's home
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Hello Folks, I am Database Architect. I enjoy teaching.
I can teach SQL Server, Power BI, MSBI (SSIS, SSAS - DAX, MDX), Azure Cloud Computing
Read more
Similar classes
arrow icon previousarrow icon next
verified badge
Olesia
I offer courses in data development / database / machine learning / data science (python):

I also offer the possibility of helping you with the realization of your academic projects.

We support you in the Data development of your business.

-1- Databases & Data warehouses (AWS / Google Cloud / Azure Cloud)
-2- Machine Learning
-3- Deep Learning (tensorflow, pytorch, RNN, CNN, LSTM)
-4- Data Processing
-5- Machine Learning design and deployment (docker, ...)
-6- Data Pipelines
-7- Google Sheets with Realtime Pipelines, Macro (VBA) & Database Connection
-8- Online dashboards on browsers or on your Excel, Google Sheets (Python, R, Power BI, Tableau, Kibana, etc.)

- Our Tech Stack -

- Databases:
AWS DynamoDB, Amazon Redshift, PostgreSQL, MySQL, multi-cube DBs (EPM / BI platform)
- Languages:
Python, Spark (Scala, Python, Java), JavaScript, CSS, HTML
- Development environment:
JSON, SQL, NoSQL, Bash Shell Scripting, Jupyter Notebook, Anaconda, REST API, VSCode, DBeaver, Google services, Platform as a Service (PAAS), Apache Airflow, Serverless Computing, SublimeText
- Clouds:
Amazon Web Services, Azure Databricks, Google GCP (Google Firebase)
- Data Lake AWS / Databricks:
EC2 (Linux), IAM, Amazon MWAA (Managed Workflows for Apache Airflow), Lambda, S3, DynamoDB, RedShift; Kibana, Azure Databricks, CloudFormation
- Web crawling / Scraping:
Python Scrapy
- Data streaming:
Airflow, Kafka
- Data visualization / ETL:
Python, Kibana, Tableau, Power BI & DAX, Excel Power Query (and lang.M)
- Continuous integration workflows (CI / CD):
Docker / Google cloud / Kubernetes; Amazon ECS)
- Containerized applications:
Docker (Docker container, Docker-compose)
- Virtualization technologies:
VirtualBox, Vmware
- Agile tools:
Version control (Git / GitLab), tickets (JIRA), Bitbukets, Trello, Wiki (Confluence), Jetbrains
- OS:
Linux, Windows
verified badge
Amine
✓ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP • Excel

✓ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

✓ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL

- Descriptive, exploratory and multivariate statistical analyses on business data

- Production of performance indicators and actionable analyses to support decision-making

✓ Selection and implementation of methods

- Preparation and structuring of databases

- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)

- Linear and logistic regressions

- Factor analyses (PCA / MCA)

- Mediation and moderation models

- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics

- Help in understanding and interpreting the results

- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)

- Multivariate analyses

- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)

- t-tests (one and two samples, independent or paired)

- Chi-square, binomial tests

- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)

- Logistic regression

- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA

- Repeated measures ANOVA

- Fixed and random effects

- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)

- Exploratory factor analysis

- Factorial rotations

- Validation and interpretation of structures and clusters

✓ Reporting & communication

- Clear, structured and concise reporting of results

- Visualizations tailored to decision-makers

- Support for strategic and operational decision-making
message icon
Contact Vivek
repeat students icon
1st lesson is backed
by our
Good-fit Instructor Guarantee
Similar classes
arrow icon previousarrow icon next
verified badge
Olesia
I offer courses in data development / database / machine learning / data science (python):

I also offer the possibility of helping you with the realization of your academic projects.

We support you in the Data development of your business.

-1- Databases & Data warehouses (AWS / Google Cloud / Azure Cloud)
-2- Machine Learning
-3- Deep Learning (tensorflow, pytorch, RNN, CNN, LSTM)
-4- Data Processing
-5- Machine Learning design and deployment (docker, ...)
-6- Data Pipelines
-7- Google Sheets with Realtime Pipelines, Macro (VBA) & Database Connection
-8- Online dashboards on browsers or on your Excel, Google Sheets (Python, R, Power BI, Tableau, Kibana, etc.)

- Our Tech Stack -

- Databases:
AWS DynamoDB, Amazon Redshift, PostgreSQL, MySQL, multi-cube DBs (EPM / BI platform)
- Languages:
Python, Spark (Scala, Python, Java), JavaScript, CSS, HTML
- Development environment:
JSON, SQL, NoSQL, Bash Shell Scripting, Jupyter Notebook, Anaconda, REST API, VSCode, DBeaver, Google services, Platform as a Service (PAAS), Apache Airflow, Serverless Computing, SublimeText
- Clouds:
Amazon Web Services, Azure Databricks, Google GCP (Google Firebase)
- Data Lake AWS / Databricks:
EC2 (Linux), IAM, Amazon MWAA (Managed Workflows for Apache Airflow), Lambda, S3, DynamoDB, RedShift; Kibana, Azure Databricks, CloudFormation
- Web crawling / Scraping:
Python Scrapy
- Data streaming:
Airflow, Kafka
- Data visualization / ETL:
Python, Kibana, Tableau, Power BI & DAX, Excel Power Query (and lang.M)
- Continuous integration workflows (CI / CD):
Docker / Google cloud / Kubernetes; Amazon ECS)
- Containerized applications:
Docker (Docker container, Docker-compose)
- Virtualization technologies:
VirtualBox, Vmware
- Agile tools:
Version control (Git / GitLab), tickets (JIRA), Bitbukets, Trello, Wiki (Confluence), Jetbrains
- OS:
Linux, Windows
verified badge
Amine
✓ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP • Excel

✓ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

✓ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL

- Descriptive, exploratory and multivariate statistical analyses on business data

- Production of performance indicators and actionable analyses to support decision-making

✓ Selection and implementation of methods

- Preparation and structuring of databases

- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)

- Linear and logistic regressions

- Factor analyses (PCA / MCA)

- Mediation and moderation models

- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics

- Help in understanding and interpreting the results

- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)

- Multivariate analyses

- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)

- t-tests (one and two samples, independent or paired)

- Chi-square, binomial tests

- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)

- Logistic regression

- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA

- Repeated measures ANOVA

- Fixed and random effects

- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)

- Exploratory factor analysis

- Factorial rotations

- Validation and interpretation of structures and clusters

✓ Reporting & communication

- Clear, structured and concise reporting of results

- Visualizations tailored to decision-makers

- Support for strategic and operational decision-making
Good-fit Instructor Guarantee
favorite button
message icon
Contact Vivek