Continuous education

At your own pace
Monthly intakes
Online

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.

Support interview

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.

Download the Executive Engineering Education catalogues

Examples of modules

Examples of Data Scientist modules:

Data Science - Initiation

 50 hrs

Data Science - Initiation  (50 hrs)

 

  • Foundations of Statistical Analysis & Machine Learning – Part 1  (25 hrs)
  • Python Machine Learning Labs  (25 hrs)

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Statistical Machine Learning – Base (75 hrs)

75 hrs

Statistical Machine Learning – Base (75 hrs)

 

  • Foundations of Statistical Analysis & Machine Learning – Part 2  (40 hrs)
  • Advanced Statistical Analysis & Machine Learning  (35 hrs)

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Neural Networks

75 hrs

Neural Networks (75 hrs)

 

  • Continuous Optimisation  (25 hrs)
  • Artificial Neural Networks  (25 hrs)
  • Deep Learning  (25 hrs)

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Statistical Machine Learning – Advanced

150 hrs

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)

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Examples of Data Engineer modules:

Data Engineering - Initiation

 50 hrs

Data Science - Initiation  (50 hrs)

  • Python Machine Learning Labs (25 hrs)
  • Data Wrangling with SQL (25 hrs)

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Cloud-Computing

100 hrs

Statistical Machine Learning – Base (75 hrs)

 

  • Amazon AWS (50 hrs)
  • Azure (25 hrs)
  • Cybersecurity (25 hrs)

 

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Big Data

75 hrs

Big Data (75 hrs)

 

  • Hadoop & Spark (50 hrs)
  • Data Pipeline – Part 2 (25 hrs)

 

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Advanced Databases

100 hrs

Advanced Databases (100 hrs)

 

  • Relational databases for ETL & Datawarehousing (25 hrs)
  • NoSQL (25 hrs)
  • Data Pipeline 1 – XML & JSON (25 hrs)
  • Semantic Web Technologies (25 hrs)

 

Apply Now

Machine Learning Engineer

200 hrs

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)

Apply Now

Examples of Data Analyst modules:

Data Analytics - Initiation

 50 hrs

Data Analytics - Initiation (50 hrs)

 

  • Python Machine Learning Labs (25 hrs) or Advanced Excel for Data Analytics & Machine Learning (25 hrs)
  • Data Wrangling with SQL (25 hrs)

 

Apply Now

Databases

75 hrs

Databases (75 hrs)

 

  • Relational databases for ETL & Datawarehousing (25 hrs)
  • NoSQL (25 hrs)
  • Data Pipeline 1 – XML & JSON (25 hrs)

 

Apply Now

Machine Learning Analyst

100 hrs

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)

 

Apply Now

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