Master of Science Data Marketing Manager

This module of Business English applied to marketing allows learners to implement and apply the right vocabulary and attitude.

• The objective is to acquire key skills in terms of budget management and reporting.
• Particular emphasis will be placed on the budget architecture, with the implementation of summary documents, project management control and its link with budget management, the execution and management of dashboards.

• This module aims to deepen the skills of learners in IT to meet the demand of companies in terms of budget or commercial monitoring, project management, personnel management and communication: Excel, Word, PowerPoint, team work tools, business software.

• This seminar is focused on a negotiation in a national and international context. 
• It will be necessary to take into account the cultural dimension and define its impact in an international negotiation.
• The national negotiation will focus on the sales process through role-playing. 

This module allows learners to improve their CV and their posture, notably through simulations (business game, professional simulation, speaking, etc.); practical and professionalizing workshops (CV, professional social networks, coaching, etc.) as well as professional and master class conferences. 

• This module aims to learn how to create a Business Plan or business plan: costed project design for business creation or development.
• Several steps are addressed: feasibility study, market targeting, opportunities and risks, strengths and weaknesses, communication, financing plan and profitability.

Through case studies, this module aims to master the tools specific to marketing and communication on the Internet, mainly addressing: 

• The latest trends in e-commerce (m-commerce / f-commerce…). 
• The integration of Web 2.0 into marketing strategies. 
• Presentation and mastery of Web analytics tools. 
• Development of a marketing and commercial strategy on the different social media. 

• Know the positioning of the company in the legal environment. 
• Know the legal constraints governing online commerce, and more broadly internet business 

• Understand the basics of programming in Python, focusing on variables, loops and data manipulation with Pandas.
• Provide a solid foundation for those who wish to evolve in data science or improve their technical skills.
• Gradually acquire the skills needed to solve real data issues.

• Overview of website creation solutions (CMS, PHP development, WYSIWYG tools…). 
• Presentation of the different analysis tools, website traffic, main indicators: origins, conversion rate, time spent… 

The objective of this course is to give an overview of the Big Data ecosystem and how these technologies can help achieve new goals through new data analysis techniques, by offering a fundamental introduction to the main components of all new technologies related to Data and its use cases in various fields.

The programming languages R and Python will be presented and implemented in order to understand their interests from a managerial point of view and thus be able to choose the most relevant analysis methods. 

Data analytics is the exploration, transformation and analysis of data in order to identify trends and patterns that reveal relevant actionable information and improve efficiency, which helps optimize decision making. A modern data analytics strategy allows systems and companies to act based on automated analyses in real time, which ensures immediate and impactful results. 

Data-driven marketing is a process used by marketers to gain insights and identify trends about consumers and their behavior – what they buy, the effectiveness of ads and how they browse. 

• Deepen your knowledge of SQL and Python for effective data management.
• Learn advanced cleaning and validation techniques to ensure the integrity and accuracy of data in a professional context.
• Discover how to transform raw data into reliable and actionable information.
• This module is essential to ensure relevant and quality data analyses.

• This module trains learners to pilot and implement a digital transformation within an organization.
• They will learn to identify digitalization opportunities, define a digital strategy aligned with the company’s objectives, manage transformation projects, support teams in change and measure the return on investment.
• Learners will acquire the necessary skills to successfully carry out complex digital transformation projects and succeed in their transition to digital.

• The economic and societal potential of data is enormous: it can enable new products and services based on new technologies, make production more efficient and provide tools to fight against societal challenges.
• Overview of the laws around data.

• From large amounts of data, coming from very diverse sources, deduce regular or potential behaviors, through modern targeting techniques, segmentation and scoring of e-consumers.
• Mastering real-time behavioral analysis to promote multi-channel promotions and influence consumer behavior directly at the point of sale (or on the website). 

• This module allows you to understand and master the challenges related to open data.
• Discover how to collect, analyze and leverage this data to develop new products, services or economic models.
• Learn to identify opportunities and challenges related to open data, as well as to comply with current regulations.
• Integrate Open Data into the company’s strategy and become a player in digital innovation. 

• Analyze large volumes of data at the right time in order to evaluate those coming from new sources, such as traffic from social media or clicks made by a prospect on a company’s website, making the targeting and segmentation of profiles as precise as possible.
• Know the consumer’s position in real time.
• Use the right tools to collect and leverage this information.
• Study analysis models and implementation simulations.
• Analyze the consumer’s attendance or purchasing behavior in order to optimize decision-making.

• Master the international regulatory environment of data management, both in terms of collection and sharing.
• Identify the different approaches to personal data protection.
• The consent of individuals on their personal data.
• Integrate the rapid changes in legislation at the state level and their impact on the use and strategies of tomorrow’s companies.

• This course explores the application of agile methods to the field of data analysis.
• It addresses the fundamental principles of these methods, such as Scrum and Kanban, and their adaptation to data projects.
• Learners will see how to manage data analysis projects in an iterative and collaborative way, define sprints, prioritize tasks, and adapt to changes.
• The focus will be on integrating agile methods with specific data science tools and techniques, in order to foster innovation and efficiency in solving complex data-related problems.

• This module will immerse you in the heart of the dynamic market for Big Data services.
• You will discover the different players, service offers, economic models and challenges of this growing market.
• You will learn to identify the needs of companies in terms of Big Data, to design customized solutions and to evaluate their economic viability.
• This module will give you the keys to position yourself as an expert in this market and seize the opportunities it offers.

• This module allows learners to improve their resume and their posture through, in particular, role-playing exercises (business games, professional simulations, speaking sessions, etc.);
• Practical and professionalizing workshops (CV, professional social networks, coaching, etc.) as well as career conferences and master classes.

• Digital makes it possible to obtain a colossal set of information on individuals.
• However, without immediate processing, this data quickly becomes obsolete.
• Know the sources of information available to the Marketer to accurately describe the situation or desires of its clients and prospects in real time.

• Analysis of study data: descriptive, explanatory or predictive analyses of simple or complex treatments.
• Textual analysis and CRM: understand the possibilities offered by textual analysis tools to apprehend data with a high degree of automation.
• Improve the quality of the database (homogeneity, qualification, management of inactive contacts, etc.).

• Deepen advanced data analysis using.
• Python and by exploiting the potential of Generative Artificial Intelligence (GenAI).
• Learn how AI techniques can improve data interpretation and communication via prompt engineering.
• Apply data processing strategies to concrete cases.
• Develop an essential critical mind to evolve in the field of data.

• Stakes of the algorithm in the value chain of companies.
• Algorithms now allow machines to learn how to detect patterns or models among millions of data: search for groups of similar elements.
• Forecasting a sequence.
• Predicting a continuous attribute.

• The programming languages R and Python will be presented and implemented in order to understand their interests from a managerial point of view and thus be able to choose the most relevant analysis methods.

• Introduce a qualitative dimension in addition to the quantitative aspect.
• This approach will explore crucial aspects such as the implementation and analysis of Heatmaps, A/B Testing, creation and refinement of audiences, implementation of Insight capture pages and retargeting.

• Data Mining is defined as a process used to extract usable data from a broader set of raw data.
• Companies can learn more about their customers and develop more effective strategies related to the various business functions, enabling them to leverage resources in a more optimal and judicious manner.

• Monitor and analyze the online data that is most relevant to the company’s activity.
• Identify the right information at the right time and place, in order to improve decision-making and optimize the organization’s performance.
• Choose the appropriate tools to understand and capitalize on this new reality.
• Anticipate changes in markets and customer behavior.
• Data Mining applied to Customer intelligence.
• Implement a Customer intelligence project in a company.

• Know the basic tools of data analysis.
• Explore, describe and interpret data in their multidimensional aspect.
• Ask the right statistical questions in line with a marketing problem.
• Perform simple statistical processing in order to issue marketing recommendations.

• Determine the value of customers and prospects by developing scores specific to an activity, based on all the data made available.
• Develop an acquisition or loyalty strategy based on the defined objectives.
• Use scoring to better target, avoid SPAM-related complaints, email unsubscriptions, and manage marketing pressure in real time.
• Beyond targeting, the real added value of data also lies in the predictability of consumer behaviors.
• Predict the future behavior of customers.
• Identify the most profitable, the most influential.

• Deepen data analysis and visualization with a focus on user experience (UX/UI).
• Train participants to use Looker Studio to create interactive and impactful dashboards, promoting better data communication.
• Turn complex data into clear visual narratives to facilitate strategic decision making.
• This course develops essential analytical skills to play a key role in Business Intelligence.

• Written exams.
• Memory defense.