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This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since February 2025
Instructor since February 2025
SQL Server, Power BI, MSBI (SSIS, SSAS - DAX, MDX), Azure Cloud Computing
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From 13 € /h
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Hello Folks, I am Database Architect. I enjoy teaching.
I can teach SQL Server, Power BI, MSBI (SSIS, SSAS - DAX, MDX), Azure Cloud Computing
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At student's location :
  • Around Paris, France
Age
Adults (18-64 years old)
Student level
Beginner
Intermediate
Advanced
Duration
30 minutes
45 minutes
60 minutes
90 minutes
120 minutes
The class is taught in
English
Availability of a typical week
(GMT -04:00)
New York
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At student's home
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
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.
Read more
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Adam
Master Algorithmic Logic and Development
Learning to program at the university or engineering school level is not just about writing lines of code: it's about learning to analyze complex problems, construct logical reasoning, and develop effective solutions. Holding a PhD in Computer Science and a State Engineering Diploma, I bring my more than 35 years of experience to bear on helping students and professionals achieve complete mastery of programming.

Expertise and Pedagogy through Practice
Whether you're preparing for an exam, a complex academic project, or a technical interview, my goal is to make you completely independent. We will work together on:

Essential languages: Python, Java, and SQL (databases).

Advanced algorithms and data structures.

Object-Oriented Programming (OOP).

Optimization, structured design and debugging of your programs.

Rather than memorizing code, you will acquire the good programming practices required in higher education and business, including the thoughtful use of assistive tools (AI) to verify and improve your solutions.

Work Environment and Requirements
Programming requires precise, interactive, and technical guidance. Therefore, it's essential to note that the course is conducted via webcam and video conference with screen sharing. This format allows us to write, test, and debug your code together in real time, ensuring extremely rapid progress.

To ensure a serious and immediate commitment to your development projects, a trial lesson or brief webcam chat is not part of my approach. We dive straight into analyzing your code and resolving your issues from our very first session.

Support Formats

60-minute session: Ideal for unlocking a specific bug, understanding a complex algorithmic concept, or correcting a targeted program.

90-minute session: Recommended for making significant progress on a university project, preparing for a computer science exam, or undertaking a complete refresher course.

I would be delighted to pass on to you the rigor and technical expertise that will allow you to excel in computer science.
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
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Contact Vivek
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1st lesson is backed
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Good-fit Instructor Guarantee
Similar classes
arrow icon previousarrow icon next
verified badge
Adam
Master Algorithmic Logic and Development
Learning to program at the university or engineering school level is not just about writing lines of code: it's about learning to analyze complex problems, construct logical reasoning, and develop effective solutions. Holding a PhD in Computer Science and a State Engineering Diploma, I bring my more than 35 years of experience to bear on helping students and professionals achieve complete mastery of programming.

Expertise and Pedagogy through Practice
Whether you're preparing for an exam, a complex academic project, or a technical interview, my goal is to make you completely independent. We will work together on:

Essential languages: Python, Java, and SQL (databases).

Advanced algorithms and data structures.

Object-Oriented Programming (OOP).

Optimization, structured design and debugging of your programs.

Rather than memorizing code, you will acquire the good programming practices required in higher education and business, including the thoughtful use of assistive tools (AI) to verify and improve your solutions.

Work Environment and Requirements
Programming requires precise, interactive, and technical guidance. Therefore, it's essential to note that the course is conducted via webcam and video conference with screen sharing. This format allows us to write, test, and debug your code together in real time, ensuring extremely rapid progress.

To ensure a serious and immediate commitment to your development projects, a trial lesson or brief webcam chat is not part of my approach. We dive straight into analyzing your code and resolving your issues from our very first session.

Support Formats

60-minute session: Ideal for unlocking a specific bug, understanding a complex algorithmic concept, or correcting a targeted program.

90-minute session: Recommended for making significant progress on a university project, preparing for a computer science exam, or undertaking a complete refresher course.

I would be delighted to pass on to you the rigor and technical expertise that will allow you to excel in computer science.
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
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Contact Vivek