Study Data Analytics, Data Science or Data Engineering by choosing one of our modular courses (RNCP certified). These courses can be taken online and at your own pace. The executive training allows you to start at any time and acquire new skills right away. As the SPOC mode, this study path is intended for professionals who wish to work and study at the same time.
Applying to one of our modular courses requires reflection and commitment. It is important in your selection criteria that the curriculum is really in line with your needs and professional projects. Thus, we offer personalised pedagogical support even before the beginning of the programme.
Before the beginning of the module, an interview with a member of the Direction of Studies takes place in order to:
Verify that the candidate has the necessary prerequisites to follow the module. If necessary, the candidate will be offered, without extra charge, videos or additional materials to get up to speed on required skills.
Confirm with the candidate the adequacy of the module with his professional objectives. If necessary, it will be possible to adjust the content of the module with other classes to fit the candidate’s needs.
Personalised learning paths
The Executive Engineering Education at DSTI are aimed at executives wishing to master the skills and tools required to develop their careers. They will be able to take advantage of the many opportunities offered by the fields of Data Analytics, Data Science and Data Engineering.
The student can choose among the different courses available to build his Data Science & AI learning path through different volumes: 50 hrs, 75 hrs, 100 hrs, 150 hrs or 200 hrs.
Examples of modules
Examples of Data Scientist modules:
Statistical Machine Learning – Base (75 hrs)
Statistical Machine Learning – Advanced
Statistical Machine Learning – Advanced (150 hrs)
- Foundations of Statistical Analysis & Machine Learning – Part 2 (40 hrs)
- Advanced Statistical Analysis & Machine Learning (35 hrs)
- Statistical Analysis of Massive and High Dimensional Data (25 hrs)
- Time-Series Analysis (25 hrs)
- Survival Analysis (25 hrs)
Examples of Data Engineer modules:
Machine Learning Engineer
Advanced Databases (100 hrs)
- Hadoop & Spark (50 hrs)
- DevOps & Continuous Integration (50 hrs)
- Foundations of Statistical Analysis & Machine Learning – Part 1 (25 hrs)
- R for Big Data (25 hrs)
- Python Machine Learning Labs (25 hrs)
- Deep Learning (25 hrs)
Examples of Data Analyst modules:
Data Analytics - Initiation
Machine Learning Analyst
Machine Learning Analyst (100 hrs)
- Foundations of Statistical Analysis & Machine Learning– Part 1 (25 hrs)
- R for Big Data (25 hrs)
- Data & Machine Learning Visualisation Ecosystem (25 hrs)
- Reporting & Visualisation – Preparation to Microsoft PowerBI Certification (25 hrs)