Data Product Manager Course

The Data Product Manager (DPM) plays a key role in analyzing and interpreting big data. His role is one of the most important in a Data Science project.
The Data Project Manager is the person in a company who tries to find a technical solution to a customer need. He is in direct contact with the teams involved to understand their expectations and problems.
He then needs to find out what resources are available to assemble a team to develop the solution.These resources may be financial, technical or material. He coordinates and supervises the members of the team to ensure that the goals set are achieved efficiently. Finally, the Data Product Manager informs his clients about the use of the solution and ensures that it is used optimally without him. The DPM is not tied to a fixed team: He works on a task basis.

He does not necessarily need to have technical knowledge, for example in the area of training algorithms, but he must be able to understand the conditions that need to be met and recognise the interests of the subject matter experts. As a coordinator, he or she must also be able to speak the language of business, as the clients are often from fields other than data science. It is therefore a cross-cutting job that requires flexibility and a diverse and varied business culture. A good manager knows what his teams are working on and is able to critically assess the quality of the results.

The Data Product Manager begins by identifying the customer’s needs, such as the desire to automate a task. Once he understands the problem, he reviews the possible solutions and coordinates the different teams. His goal is to develop a clear, fast solution tailored to the customer. He must fit into the team’s strategy and respect their way of working.

One of his main tasks is to analyze market data to identify new product opportunities. He uses data science and data engineering techniques to design and develop products that meet consumer expectations.

They also use data warehousing and data visualization to improve product strategy. He/she will develop data pipelines to prepare collected data for analysis.

He/she will also analyze data from products already on the market, using techniques such as A/B testing and multivariate testing to prepare the next iteration of a product.

Finally, once the various resources have been put in place, he/she must monitor and develop the product. The solution must be implemented within the team, in response to a need that may be ad hoc, but must be integrated into the daily practice of the staff.

There are many ways in which companies can benefit from the Data Product Manager. He makes it possible to use real-time data sources to develop new products, improve existing products or enhance the user experience.

Product teams no longer have to rely on intuition or guess how customers will interact with a product, as the information provided by data analytics enables prototyping and testing in advance.

In addition, a data product manager eliminates the risk of using outdated or corrupted data to make decisions. For all these reasons, the data product manager is increasingly sought after by companies in all industries.

Salaries are correspondingly attractive. According to Glassdoor, a data product manager in the US earns an average of more than $110,000 per year. In France, according to Talent.com, the average annual salary for the job is more than €60,000.

And there is no end in sight to the strong demand. According to Zippia, the number of job openings will increase by 8% per year until 2028 – to over 20,000 in the US alone!

The curriculum consists of several modules, which are divided into different learning units.
The units for Data Scientist training are structured as follows:

– Business Intelligence
– Acculturation and Data
– Governance
– Project management
– Python
The total duration of the training is 115 hours – 85 hours of training and 30 hours for the project.

At the end of your training you will achieve 4 competencies:

– Skill 1: Development of an artificial intelligence solution with design thinking
– Skill 2: Management of an artificial intelligence project
– Skill 3: Developing artificial intelligence (machine and deep learning)
– Skill 4: Implementation of an artificial intelligence solution
You must be proficient in all 4 competencies to achieve the full certification.

Acquisition of a competency block is final. The validation of a block is confirmed by a certificate of achievement, which is an important signal on the job market.

Throughout your training, and as your skills are developed, you will carry out a data science project. 

This project may come from our catalog, composed of various subjects, with technical business issues and using rich and complex data. You can also propose a personal project, as long as the data is accessible and our teaching team validates it.

It is an extremely effective way to move from theory to practice and to ensure that you apply the themes covered in class.
It is also a project highly appreciated by companies because it ensures the quality of the training and the knowledge acquired at the end of the Data Scientist training since the use of soft-skills is also very present.

– Ability to transmit information
– Know how to present and popularize your work
– Know how to highlight data with interactive tools (Dashboard, Streamlit, etc.)
 
It is a project that will require a real investment: at least a third of your time spent on training will be on this project.

The project is supervised by a DataScientest mentor who will regularly discuss with you to ensure your progress and to guide you.

If we refer to the Data managers of the big CAC 40 groups, it is more important for an MLOps to know how to communicate in writing and orally, than to master the company’s own business.
Therefore, we have integrated into our curriculum modules that allow you to practice these soft skills with:

– Oral presentations of the project, which allow developing these skills.
– Masterclasses dedicated to project management and results interpretation.
– Masterclasses on best practices in data visualization and dedicated tools.
You will also have the opportunity to participate in CV workshops and career coaching via DataScientest’s career managers.

The results are assessed using a procedure designed to determine whether the student has acquired the skills needed to become a Data Product Manager.

The teaching team will evaluate two aspects

– Professional situation involving project development with an estimated duration of 30 hours.
– Practical online case studies to apply theoretical knowledge on a regular basis.
 
The teaching team assesses students by carrying out work-related projects. These projects correspond to the phases of the tasks of a data project manager. Students learn and produce strategic reports.They are assessed on the quality and relevance of the results.There are currently 9 projects to be completed.

You can therefore benefit from the recognition of a world-class school in the fields of innovation, mathematics and digital engineering. IAs the B2B leader in Data Science training, DataScientest is highly regarded by companies that entrust it with the training of their teams in Data Science

As the B2B leader in Data Science training, DataScientest is highly regarded by companies that entrust it with the training of their teams in Data Science.

Thanks to the validation of competences developed during our Data Product Management training, you can obtain the nationally recognized certification “Artificial Intelligence Project Manager”, opening many doors in the job market.

You must be proficient in all 4 competencies to achieve the full certification:
– Competence 1: Development of an artificial intelligence solution with design thinking
– Competence 2: Management of an artificial intelligence project
– Competence 3: Developing artificial intelligence (machine and deep learning)
– Competence 4: Implementation of an artificial intelligence solution

Depending on the industry and company, the salary of a Data Product Manager ranges from 45 000 € to 55 000 € per year, according to Glassdoor.

Our Data Product Manager course will provide you with the necessary skills, such as the Python programming language or Business Intelligence with Power BI, to take your data further with our Data Analyst course.

Visit our dedicated page to find out more.

After completing the Data Product Manager course, you can continue your training with the Data Analyst course.

You can also take the official Microsoft Power BI PL-300 certification and become a “Microsoft Certified Power BI Data Analyst Associate”.

After your registration on our website, we will contact you and give you a presentation of DataScientest. We will discuss your background and your wishes and give you an overview of what we offer. The idea is to align your expectations with our training courses.

Afterwards, we will redirect you to our placement test. It will allow us to know your background and your mathematical / data science level.

Once you have passed this test, a member of the admissions team will contact you to discuss your results and validate your professional project, your motivations and finally the relevance of your educational project.

Once your project is confirmed, you will go through the registration phase with our teams who will initiate your MLOps training and set it up with you in all its aspects.
Of course you can always book a meeting with one of our counselors now, click here!

Our teams are sensitive to your time constraints and will assist in the processing of your application as quickly as possible. We try to limit the processing time to a maximum of one week. If you’re motivated and confident about what you want to achieve, you can register within a day!

DataScientest is the only company offering hybrid training.

This translates into 85% learning on the coached platform and 15% masterclass session by videoconference in order to combine flexibility and rigor without compromising on one or the other. It is a carefully considered choice that motivates our pedagogy to allow quality learning while maintaining your motivation.

Discover our pedagogical approach in this video.

In order to integrate the Data Product Manager training, it is necessary to have obtained a diploma or a level 6 title (equivalent to a bachelor’s degree)

These prerequisites exist because although the training is focused on data science, and not mathematics, they are necessary for a good understanding of the concepts covered.

Learners are also required to have a computer with an internet connection and a webcam in order to follow the training in an optimal way.

DataScientest examines all possibilities of adaptation (pedagogical, material, technical and personnel) to compensate for your disability and to enable you to train under good conditions. If you have any questions about your situation, you can contact our disability officer: [email protected]

You can pay for your training in 3, 6, 10 or 12 monthly rates.

Our teams are there to guide you, whenever you have a question.

You can find all financing options on this page!

Obviously ! And who better to provide support than our teachers, who also designed the program. They are available and attentive to all questions, whether theoretical or practical and will be able to demonstrate pedagogy in their response.

In addition, to ensure everyone’s completion and commitment, our teachers follow your progress closely. As soon as you stop logging in for an extended period, your cohort manager will hear from you: we won’t let you down!

Finally, our papers, exams and defenses are also corrected by hand by our panel of qualified teachers: everything is done so that everyone can progress effectively at their own pace. At DataScientest we are convinced that only personalized monitoring ensures quality learning!

On the first day of your training, you will be presented with a platform dedicated to career services, containing all the workshops essential to your job search.
You can access it continuously, even after the end of your training.

Estelle and Morgane, our career managers, are entirely dedicated to you throughout your training. It is possible to make an individual appointment with one of them to accompany you and answer your questions about your career plan.

Each month :

– A full day is organized to help you optimize your job search with different topics on presentation, career change, salary negotiation and technical test training. In addition to these topics, other workshops are organized according to your needs.
– You will benefit from a career workshop with the intervention of a senior expert consultant.
– Different topics to help in the job search are discussed: how to fight the imposter syndrome, how to create a network, how to write a good CV and LinkedIn oriented Data.
– Participate in an “Alumni Talk”. An alumnus speaks to share his experience of training, job search and give you tips.
On the other hand, concrete actions are set up to help you in your job search: the recruitment fair organized by DataScientest with its partner companies, organization of webinars with data experts, communication actions to boost your visibility (CV contest, DataDays, project articles published on the blog and external reference media).

Finally, you should know that a specific Slack channel has been set up for people looking for a job, on which all the information about workshops and job offers are transmitted.

To learn more about DataScientest’s career support activities, click on this link.

Newsletters developed by our data scientists are sent regularly and are a reliable source of specialized data science information.

At the same time, the DataScientest community continues to grow, and with it all of its alumni.

To keep in touch and allow former students to communicate with each other, DataScientest has set up a group of alumni on LinkedIn  who share and discuss various themes around Data Science.

The DatAlumni community is a LinkedIn community that brings together DataScientest alumni. On this page, questions, tips, and technology news are shared on this page for the benefit of all. You will be invited to join it at the beginning of your training.

This makes it possible to create strong links with the major groups, which have ensured the growth of our structure.

Initially, DataScientest supported the data transition of companies. This has made it possible to create strong links with the major groups which have ensured the growth of our structure.

Subsequently, they are the ones who motivated the launch of our offer to individuals in order to compensate for the lack of competent profiles. This need for good profiles is reflected in the survey we conducted among 30 CAC 40 groups. Even if they had tight budget constraints, only 4% believe they would downsize their data scientist workforce; by comparison, 28% would still seek to increase their number by more than 20%.

Thanks to our experience with large companies, we regularly organize recruitment fairs for all our students and alumni with our partner companies.