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 August 2022
Instructor since August 2022
Translated by GoogleSee original
Python for data analysis enthusiasts
course price icon
From 38 € /h
arrow icon
This course will allow you to have Python language skills for data analysis and visualization.
During this course, you will have the opportunity to use and manipulate the most famous Python libraries such as Numpy, Matplotlib, Seaborn, Pandas, Scikit-Learn, etc. Finally, the methodology is based on familiarization with Python syntax and putting the acquired skills into practice in projects.
Python is the most widely used programming language in the world. It is the reference programming language in the scientific community since it allows the creation of a multitude of scientific applications.
Extra information
The participant will need a computer or tablet.
Location
green drop pin icon
|
Use Ctrl + wheel to zoom!
zoom in iconzoom out icon
location type icon
At teacher's location :
  • Fresnes, France
location type icon
Online from France
About Me
With over 4 years of experience in Data Science and over 5 years in Python, my passion for this field really grew during my first programming applications. That's when I decided to specialize in Data Science.

Thanks to my various professional experiences, I had the opportunity to work on various projects, using Python, Deep Learning, and Machine Learning to solve complex problems. I thus acquired expertise across the entire Data Science value chain, from data acquisition and management to the deployment of artificial intelligence models.

I am also an open-minded, responsive and always curious person. For me, constant learning is essential, and I always strive to set ambitious goals to advance in my career.
Education
Having a master's degree from Sorbonne University - Sciences & Engineering, and a master's degree in Data Sciences & AI. Today I am a Data Scientist at BPCE.
Experience / Qualifications
Data Scientist (Natixis)
Data Scientist (SOCOTEC Monitoring)
Data Scientist (Tunisian Petroleum Activities Company)
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
45 minutes
90 minutes
120 minutes
The class is taught in
French
English
Arabic
Availability of a typical week
(GMT -05:00)
New York
at teacher icon
At teacher's location and via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
This course will allow you to acquire SQL skills for data analysis and management.

During this course, you will have the opportunity to use and manipulate the most well-known SQL features such as joins, subqueries, aggregation functions, filter and grouping clauses, as well as transactions. Finally, the methodology is based on familiarization with SQL syntax and the practice of acquired skills through real-world projects.

SQL is one of the world's most widely used languages for relational database management, and it is essential for efficiently manipulating and extracting data in many fields, including data science and business intelligence.
Read more
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
message icon
Contact Oubaid
repeat students icon
1st lesson is backed
by our
Good-fit Instructor Guarantee
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
Good-fit Instructor Guarantee
favorite button
message icon
Contact Oubaid