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Since August 2014
Instructor since August 2014
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Doctoral student in Paris 1 offers R | Python course for data science
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From 36 € /h
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I am currently in my last year of doctorate. I wrote two textbooks on data science, a first one devoted to R and data analysis. A second on the creation of deep learning model with Tensorflow.
It seems important to be able to transmit this knowledge to calmly approach data science.

Regarding my teaching experience, I was ski instructor for 5 years and profes

My teaching method is based on the use of Jupyter notebooks and online collaboration tools to optimize the exchange.

The whole of the courses is done around practical cases with a first part devoted to the theoretical notions.

All courses will be available online.

The idea is to propose a training to master the whole chain of value of the data analysis:

1: Database connection

2: Collaborative platform creation

3: Knowledge programming language to set up the analysis

4: Discovering analytics tools: capturing the best story behind the data

5: Report Writing / Collaborative Dashboard

6: Sharing the analysis with the outside world (via Medium, blog / website, and other tools.


The audience is mainly graduate students or professionals wishing to develop knowledge in data science.
Location
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At student's location :
  • Around Le Kremlin-Bicêtre, France
About Me
PhD candidate, intuitive and results-oriented. Master the integration of machine learning algorithms, structures and data analysis. Skillful at applying machine learning techniques and statistical modeling techniques to solve technical problems. Proven success in providing companies with research and solutions. Excellent communication, attention to detail and problem solving

Quality
Excellent analytical analytical skills and demonstrated ability to read and interpret
different data

Ability to communicate detailed statistical and scientific results intended for
profane. Agile in learning skills and participating in new process solutions

programming languages and software such as Python, R, TensorFlow, BigQuery, Docker, GitHub, Web Scrapping, SQL, STATA, LaTex, VBA, PowerQuery, Power BI, Access
Education
PARIS 1 and FUDAN UNIVERSITY, (FRANCE and CHINA) 2015 - 2018 |
PhD Candidate International Trade (Taught in Chinese and English)
Study topic: Econometrics, Foreign Direct Investment, Export and Quality
Subject: "Economic Complexity and Location of Foreign Firms in China"
Subject: "Promoting Upgrading: The Role of Governmental Interventions in China"
Subject: "The Role of the VAT Rebate on the Process of Quality Upgrading, Evidence from China"
UNIVERSITY PARIS 1 PANTHEON SORBONE - ENS CACHAN (with honors) | 2014 |
Master 2 International Trade Research (taught in English)
Master Thesis: "Economic Complexity and Location of Foreign Firms in China"
Experience / Qualifications
Freelance Missions | Jul 2016 - Present |

Textbook Editor Introduction to R for data analysis
Textbook Editor Artificial Intelligence with TensorFlow

Case 1: Prediction of volatility with the GARCH family model

Using the GARCH model to make the FCHI market index a volatility forecast
robust
Using the Markov-Switching GARCH model to improve performance in a market
with structural breaks

Case 2: Predict the best time to post a message on Weibo (Chinese tweeter)
Using Hurdle negative binomial model to improve prediction performance
when the dependent variable to an excess of zero.
Using Latent Class Model to Cluster Weibo Accounts

Case 3 Problem: Lack of data to calculate the margin of a company producing kitchens
tailored.
Creation of an ergonomic file on Access to enable the collection and analysis of data
Development of a model with a neutral position to obtain a real-time sales price
Implementation of a traceability of purchases / sales to know precisely the margin on each sale
Creating a monthly report
Result: + 10% margin improvement after one year

Other projects
Oversee the creation of a customer retention Dashboard: model customer repeat rate and
CLV with Pareto / NBD model
Supervise the drafting of a project for a tender: Modeling the demand for
an amusement park based in Beijing: Generalized Bass Model and other Machine Learning method
Oversee the writing of a statistical analysis after the collection of survey data for the launch of a product in China: Chi test, confidence interval, ANOVA
Age
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
60 minutes
The class is taught in
English
French
Reviews
Availability of a typical week
(GMT -05:00)
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
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Amine
◾ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP

◾ 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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Similar classes
arrow icon previousarrow icon next
verified badge
Amine
◾ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP

◾ 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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