Training Catalog Home Training Training Catalog Here you will find our ‘off-the-shelf’ training catalogue. Some of these courses will help you master specific skills such as courses focused on software functionnalities, or specific others can be combined in order to compose a real modular training scenario that allow you to smoothly gain confidence and expertise. All our training courses can be provided as on-site courses, i.e. for a particular person, team or organization: we can adapt to your constraints and objectives and design tailor-made courses. Many of the training courses here described are also offered as public attendance sessions, meaning that you can individually register for a shourt courses scheduled and held in our Training Center or online. Although the information available for each of these training courses tends to be exhaustive, if you have questions or doubts about the level or prerequisites to attend a session, we will be happy to guide you : do not hesitate to consult us to design together the best options for your training project NB: Our public attendance sessions are held for the time being online (virtual classrooms). Whilst registering to these sessions, you can benefit from our dedicated digital training platform (LMS): a space where you learn all there is to know about the training course scheduled, access educational material, attend sessions, discuss with other attendees and sometimes assess your skills. Analysis Modular training course - NVivo Advanced Discover Modular training course - NVivo AdvancedDiscussing with participants on their NVivo practices and deepen the following knowledge and skills: Mastering the NVivo environment. Source management Case management Source coding Queries and matrices Documenting your analysis; memos, annotations and links to. Viewing and exporting Importing and using data from social networks and the web Collaborative work and coding comparison. Please contact us if you would like to have this training course held in English. 1 half-day of 3 hours and 6 modules of 2 hours First ½ Day (3 hours) Review of the basic principles of qualitative analysis with NVivo. Discussion with participants on their practices. Reminder of previous course if needed Six Modules The generation and use of cases (2h) Queries: Deepening the understanding of one’s corpus and its coding (2h) Automatic queries and collaborative work (2h) Documenting one’s analyses, work and visualizations (2h) Working from web data (2h) The literature review with Nvivo and discussion about publishing with Nvivo (2h) Analysis Coaching Short courses On-site courses Short courses On-site courses Remote/Virtual Face-to-face Remote/Virtual Face-to-face English French Modular training course - NVivo basics Discover Modular training course - NVivo basics Understand the role of NVivo in the qualitative analysis process. Understand and master the NVivo environment. Source management Case management Source coding Crossing matrices Documenting your analysis; memos, annotations and links to. 1 half-day of 4h 4 additional 2-hour modules Training program First Half Day: Qualitative analysis with NVivo and getting started with the software (1h) Reminder of the basic principles in qualitative analysis The place of qualitative analysis software in the research process Nvivo its interface and philosophy The preparation of a project (1h) Preparation of sources, organization of the software and import of sources (textual data in word and pdf and images) The NVivo mind map: brainstorming as a starting point for coding Practical exercises Deductive and inductive coding (2h) Practical exercises on textual and image databases. The different coding logics. The relations Module 1: The special treatment of audio and video data and transcription (2h) The different types of transcription. Exchange between participants on their practices. The tools to carry out a transcription efficiently Demonstration of NVivo transcription I Importing a transcription made outside of NVIVO Module 2: Automatic queries (2h) Automatic coding of emotions and themes Automatic coding based on document structure – working with semi-structured and structured interviews Module 3: Working with surveys and data tables (2h) Importing Excel files Automatic coding of data tables Module 4: Documenting your analyses, your work + Crossover matrices (2h) Memos and annotations Links to Internal links Crossover matrices to explore the links between ideas Analysis Coaching English English French Stata Lasso Discover Stata Lasso How to master Lasso (least absolute shrinkage and selection operator) methods with Stata for prediction and/or inference on causal parameters. This regression method (typically used in high-dimensional problems) consists of penalizing the absolute size of the regression coefficients. Please contact us if you would like to have this training course held in English. Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Analysis Change Management Agile Management of scientific projects Discover Agile Management of scientific projects Addressing the Agile mindset and concepts . Why move to Agile ? Introduction to Agile The vocabulary of Agile The principles of Scrum Change Management Innovation with Design thinking Discover Innovation with Design thinkingUnderstand the Design Thinking process in order to use it to innovate and solve complex problems. 1.discover: discover the challenge 2.define : define precisely the problem to be solved 3.develop : imagine the most relevant solution 4.deliver : build the solution and collect feedbacks according to an iterative approach Change Management Chemistry and biology High-throughput sequencing and microbial ecology Discover High-throughput sequencing and microbial ecology Understand high-throughput genomic sequencing. Be able to choose the appropriate technology for your project. Know the bioinformatics tools used. Know the possible statistical analyses. Chemistry and biology Chemistry and biology Laboratory processes and applications Laboratory processes and applications Laboratory processes and applications Laboratory processes and applications Jump Start Signals Notebook Discover Jump Start Signals NotebookChemistry and biology Data Science First steps with R Discover First steps with R Discover the R language and software and learn the first basics of this language R1: First steps in R Introduction Entering a command in the console Writing a clean, structured and commented script Create, modify, view and delete an object Manipulating different data types and data structures The R objects: vectors, factors, arrays, lists, data frames, functions R2: Import, control and export data arrays View and edit working directory Import data contained in a .csv file Check the types of its variables and modify them if needed Categorical variables: factors Controlling for missing data Exporting a data table to a .csv file R3: Numerical valuation of data Manipulating your dataset (selecting variables, rows …) Numerical valuation: getting to know the dataset, summarizing and quantifying the information Descriptive statistics, counts, pivot tables Data aggregation (statistics by group of observations) R4: Graphical valuation of data Creating basic graphs: histogram, scatterplot, box plot, bar chart, pie chart Changing the various basic chart options (color, title, point and line type, size, …) Add elements to a chart (points, lines, segments, legends, …) Save a graph Data Science Data Science Data Science Data Science Data Science Data Science Data Science Data Science Data Science Data Science Data Science Data Science Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Face-to-face Time Series with R Discover Time Series with RPlease contact us if you would prefer to have this training course held in English. Data Science Blended Econometrics / Finance Discovering Stata software: Stata Deb1 - Stata Deb4 Discover Discovering Stata software: Stata Deb1 - Stata Deb4 Mastery of the basic functions in order to be autonomous with Stata on the following subjects: Descriptive statistics, graphs and first estimates. 4 modules of 3.5 hours each Stata Deb1 : Meeting the software Presentation of the software environment How to set up a Stata session to be efficient The general syntax of a Stata command How to use the help to become autonomous Commented example of a Stata session to understand its possibilities Importing data, describing them and visualizing them: a first approach A first exercise Stata Deb2: Working with your data Exploring a data file: the if, by and in conditional Manipulating variables: creation, recoding, labels and many other tricks Handling data: sorting, deleting, merging, changing format and producing aggregated data An exercise to test yourself Stata Deb3: Descriptive Statistics, Tables and Charts Descriptive statistics Synthetic statistical tables Univariate analysis An introduction to analysis of variance Graphs with Stata A synthetic exercise Stata Deb4: An introduction to regression Linear regression: estimation, post-estimation, diagnostics and tests Logistic regression: estimation, post-estimation, diagnostics and tests Discovering programming: loops Synthetic exercise (continued) Econometrics / Finance Theoretical and applied statistics Stata, Datetimes treatment and times series analysis (Series Temp 1 & 2) Discover Stata, Datetimes treatment and times series analysis (Series Temp 1 & 2) Processing and Analyzing Time Series with Stata. Please contact us if you would like to have this training course held in English & for the whole program. Econometrics / Finance Engineering and development Development Environment in Data Science Discover Development Environment in Data ScienceUnderstand the data science ecosystem and know the tools related to the realization of a data science project. Detailed training program DAY 1 The unix environment, interacting with a shell, open source tools (sed, awk, grep, jq, csvkit, etc.), R and Python, SQL and NoSQL Revision control and collaborative work with Git The methodology for managing a data science project Software engineering fundamentals and best practices DAY 2 Information gathering and processing (experimental designs and clinical trials, surveys and polls, web data, open data) Distributed architecture and database, map-reduce, big data, Apache Spark Engineering and development DOE with Design Expert Discover DOE with Design ExpertPlease contact us if you would prefer to have this training course held in English. Engineering and development Laboratory processes and applications Coaching Coaching Coaching Consulting Coaching Laboratory processes and applications DOE with Design Expert Discover DOE with Design ExpertPlease contact us if you would prefer to have this training course held in English. Engineering and development Laboratory processes and applications Coaching Coaching Coaching Consulting Coaching High-throughput sequencing and microbial ecology Discover High-throughput sequencing and microbial ecology Understand high-throughput genomic sequencing. Be able to choose the appropriate technology for your project. Know the bioinformatics tools used. Know the possible statistical analyses. Chemistry and biology Chemistry and biology Laboratory processes and applications Laboratory processes and applications Laboratory processes and applications Laboratory processes and applications Open Source Python - Advanced Discover Python - Advanced Deepen the tools to represent and manipulate complex data, effectively use the pandas library, import data sources (CSV, JSON, XML, SQL), perform a simple or multiple linear regression model with the statmodels library, perfect your knowledge of matplotlib and know how to use seaborn or plotly.. At the end of this training, the participant should be able to import or even merge structured or unstructured data sources, apply advanced processing on quantitative and qualitative data and build elaborate static or dynamic graphs. DAY 1 Advanced Data Processing: The numpy library : advanced functions (views, slices) the interface with scipy The pandas library: The import of external data sources, The aggregation of data, The reshaping, Indexing, The merging of data sources The statmodels library: Single and multiple regression, The testing of regression coefficients, The diagnosis of the model, Point and interval prediction The processing of strings, regex Date processing and time series management DAY 2 The generators, itertools, lazy evaluation The database interface (SQL, NoSQL) The Seaborn package:Advanced graphing features (trellis graphs, statistical distributions, heatmap) Interactive graphics with the Bokeh and Plotly packages. Open Source Python - basics Discover Python - basics Understand how data is represented, know how to manipulate simple data structures, master the basics of the numpy and scipy libraries for numerical computation and basic statistical functions, learn the basics of graphical visualization with matplotlib. At the end of this training, the participant should be able to write simple analysis scripts working either with artificial data or with data sources that do not require major pre-processing. He/she will know how to implement the main statistical tests for the comparison of two samples and perform basic exploratory graphs. Day 1 The working environment: Python 2 and 3.x, The presentation of the different consoles and debugging in Python : Anaconda Jupyter Spyder Data types: lists, dictionaries Control structures The functions, methods and packages DAY 2 Data handling and cleaning: numpy: Basic objects and manipulation of 2-dimensional arrays (array and numeric calculation functions, random number generators) scipy: Basic functionality (scientific functions and basic statistical tests) The probability distributions and univariate statistics. matplotlib: basic features: scatterplot, box plot, histogram Simple scripting Open Source Open Source Open Source Open Source Open Source Open Source Open Source Open Source Open Source French French French French French French French French French French French French French French French French French French French French French French French French French Publishing Citavi : bibliographic and reference management Discover Citavi : bibliographic and reference management Creating your Citavi project Organize and manage your references with Citavi Feed its database with new references through different exports: DOI, PDF, websites,… Cite its bibliographic references with Citavi and publish documents with Word, articles containing bibliographic references Exchange and share one’s references and knowledge items Introduction to Citavi: theoretical presentation (30 min) Starting with Citavi: Discovering the interface and working on a project (create, open, save), Collaborating with Citavi: applied exercises (1h30) Feeding the project : Adding references (manually, automatically), Searching and then inserting references (from Citavi, from the Internet, with the Picker) : concrete exercises with imports of different document formats, browsing the Internet to search for new documents (1h30) Organize and plan : Structure and sort your references (ranking, filter, table) , Search in your project (in references and full text), Modify your references (fields, linked documents, keywords, evaluation), Plan your work (tasks) : presentation and practical exercises, case study (1h) Enriching with knowledge elements: using the knowledge organizer, working on one’s PDFs (annotations), Adding thoughts to the project, Linking an article and its review: applied exercises (1h30) Exploiting your project: Using citation styles Exporting references (clipboard, text file, spreadsheet, via email) Creating a project bibliography Writing documents with Word theoretical presentation and practical application (1h) Publishing Publishing Allemand Italien Set up a scientific and technological monitoring in an innovative project Discover Set up a scientific and technological monitoring in an innovative project Succeed in the implementation of scientific, technical and technological monitoring for a project. Know the watch cycle and organize your monitoring plan. Organize the different stages of the monitoring concretely. Publishing Scientific communication and writing Oral communication in English for scientific conferences Discover Oral communication in English for scientific conferences Be able to speak in English with confidence in front of a scientific audience Know how to use your body (breathing, stance, posture, gestures) to pace your speech Know how to project yourself into the space and attract the attention of the audience by giving authority to your speech Identify one’s weak and strong points with the help of other participants Know how to summarize information to make it more dynamic Know how to use your presentation as a springboard to express yourself, not a crutch Prepare an argument to back up your speech and answer questions quickly Be more fluid in English and handle questions. Scientific communication and writing Scientific communication and writing Scientific communication and writing On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses On-site courses Writing science for publication Discover Writing science for publicationScientific communication and writing Short courses On-site courses Remote/Virtual Face-to-face Theoretical and applied statistics Discovering Stata software: Stata Deb1 - Stata Deb4 Discover Discovering Stata software: Stata Deb1 - Stata Deb4 Mastery of the basic functions in order to be autonomous with Stata on the following subjects: Descriptive statistics, graphs and first estimates. 4 modules of 3.5 hours each Stata Deb1 : Meeting the software Presentation of the software environment How to set up a Stata session to be efficient The general syntax of a Stata command How to use the help to become autonomous Commented example of a Stata session to understand its possibilities Importing data, describing them and visualizing them: a first approach A first exercise Stata Deb2: Working with your data Exploring a data file: the if, by and in conditional Manipulating variables: creation, recoding, labels and many other tricks Handling data: sorting, deleting, merging, changing format and producing aggregated data An exercise to test yourself Stata Deb3: Descriptive Statistics, Tables and Charts Descriptive statistics Synthetic statistical tables Univariate analysis An introduction to analysis of variance Graphs with Stata A synthetic exercise Stata Deb4: An introduction to regression Linear regression: estimation, post-estimation, diagnostics and tests Logistic regression: estimation, post-estimation, diagnostics and tests Discovering programming: loops Synthetic exercise (continued) Econometrics / Finance Theoretical and applied statistics Using Stata Effectively: Data Management, Analysis, and Graphics Fundamentals Discover Using Stata Effectively: Data Management, Analysis, and Graphics Fundamentals Become familiar with three main components of Stata: data management, data analysis, and data visualization. Upon completion of the course, you will be able to use Stata efficiently for data management, basic analyses and graphics. You will be able to create reproducible analysis, for better collaborative works and simplified follow-up analyses Program : Fundamentals of Using Stata (1h30 – Day1) Keeping organized Knowing how Stata treats data Using dialog boxes efficiently Using the Command window Saving time and effort while working A sample Stata Session Getting Help Basic Data Management in Stata (3h30 – Day1 and Day2) Reading Data in Stata Using and Saving Stata data files Reading in datasets of various standard formats, such as those from spreadsheets or databases Labeling data, variables and values and setting up encoded variables Creating and Recoding variables in an efficient fashion Generating statistics within groups, and working across variables Intermediate Data Management in Stata (2h – Day2) Combining datasets by adding observations and by adding variables Reshaping data from wide to long Reshaping data from long to wide Collapsing data across observations Workflow (1h30 – Day3) Using menus and the Command window to work quickly Setting up Stata for your profile Keeping complete records of what is done inside Stata: saving dofile Creating reproducible analyses, which are completely documented Finding, installing, and removing community-contributed extensions to Stata Customizing how Stata starts up and where it looks for files Analysis (3h30 – Day3 and Day 4) Using basic statistical commands Reusing results of Stata commands Using common postestimation commands Working with interactions and factor variables Graphics (2h – Day 4) Introduction to graphics Overview of graph two-way plots Building up complex graphs Using the Graph Editor Theoretical and applied statistics Theoretical and applied statistics Theoretical and applied statistics Theoretical and applied statistics Theoretical and applied statistics Theoretical and applied statistics Theoretical and applied statistics View upcoming training sessions calendar Filters Software Category Analysis Change Management Chemistry and biology Data Science Econometrics / Finance Engineering and development Laboratory processes and applications Open Source Publishing Scientific communication and writing Theoretical and applied statistics Type Coaching Consulting On-site courses Short courses Modalities Blended Face-to-face Remote/Virtual Language Allemand English French Italien Are you looking for information about a training course? You want to set up a customized training session? Contact our pedagogical team! Notice: JavaScript is required for this content. Upcoming trainings Analysis Modular training course – NVivo basics Objectives Understand the role of NVivo in the qualitative analysis process. Understand and master the NVivo environment. Source management Case management Source coding Crossing matrices Documenting your analysis; memos, annotations and links to. 19, 20, 22 and 23 September Register Ask for a quote Upcoming trainings Analysis Modular training course – NVivo Advanced Objectives Discussing with participants on their NVivo practices and deepen the following knowledge and skills: Mastering the NVivo environment. Source management Case management Source coding Queries and matrices Documenting your analysis; memos, annotations and links to. Viewing and exporting Importing and using data from social networks and the web Collaborative work and coding comparison. Please contact us if you would like to have this training course held in English. 07, 08, 09 and 10 November Register Ask for a quote Upcoming trainings Scientific communication and writing Writing science for publication 14, 15, 17 and 18 November Register Ask for a quote Previous Next