This session: 19 - 23 Jul 2027
This Certificate in Data Science (CDS) session in Paris (France) runs from Monday 19 July to Friday 23 July 2027 (week 29, Q3 2027). It is the 2nd of 3 dates in Paris (France) in 2027, at a fee of £5,900, the same for each of them. Registration is open for this date. It is held in person.
| Dates | Monday 19 Jul – Friday 23 Jul 2027 |
|---|---|
| Week | 29 of 2027 |
| Duration | One week |
| Fee | £5,900 |
| Status | Open for registration |
| Format | In person |
Previous date: 3 - 7 May 2027 Next date: 13 - 17 Sep 2027 Other dates for this course
Introduction
In today’s data-driven era, Data Science has become one of the most in-demand disciplines across industries aiming to enhance analytical capabilities and enable evidence-based decision-making.
The Certificate in Data Science (CDS) offers a practical and comprehensive training framework designed to equip professionals with the skills to extract actionable insights from large datasets using advanced tools and methods.
This program targets executives, team leaders, and professionals from various departments within both government and private sector organizations across the MENA region.
It is also ideal for early- to mid-career employees seeking specialization and senior management looking to adopt digital transformation and leverage data for strategic value.
The course offers a balanced mix of theoretical knowledge and hands-on practice, positioning it as a strategic step toward building future-ready, data-driven organizations.
Course Objectives
- Understand the core concepts of data science.
- Explore the data science project lifecycle from data collection to model deployment.
- Use data analysis tools for data cleaning and exploration.
- Apply machine learning algorithms to real-world datasets.
- Build predictive models with practical business applications.
- Interpret and visualize results through interactive dashboards.
- Evaluate and optimize model performance.
- Integrate data science outputs into organizational decision-making.
Course Outlines
Day 1: Introduction to Data Science
- What is data science and why it matters.
- Key skills required for data science roles.
- Overview of the data lifecycle.
- Types and structure of data.
- Introduction to common data science tools and languages.
- Hands-on: analyzing basic datasets.
Day 2: Data Analysis and Cleaning
- Exploratory Data Analysis (EDA) techniques.
- Identifying and handling missing values.
- Detecting and processing outliers.
- Data transformation and feature engineering.
- Visualizing patterns using charts and graphs.
- Practical session using industry-standard tools.
Day 3: Modeling and Predictive Algorithms
- Choosing the right model based on data type.
- Applying regression, classification, and clustering algorithms.
- Splitting data into training and test sets.
- Evaluating accuracy and recall metrics.
- Addressing modeling issues: bias, variance, overfitting.
- Case study: building a business prediction model.
Day 4: Data Visualization and Business Insights
- Designing interactive dashboards.
- Using tools like Python or Power BI for visualization.
- Creating executive-level reports.
- Presenting insights to stakeholders.
- Telling stories through data.
- Framing recommendations based on findings.
Day 5: Final Assessment and Organizational Integration
- Reviewing each phase of the hands-on project.
- Presenting and critiquing participant models.
- Strategies to embed data science in operations.
- Providing individual development plans.
- Final test to assess learning outcomes.
- Open feedback and discussion session.
Why Attend this Course: Wins & Losses!
- Build strong data literacy and analytical capabilities.
- Support data-informed decision-making.
- Improve operational efficiency with automated analytics.
- Enhance professional value and career growth.
- Apply data tools directly in your workplace.
- Stay current with global digital trends.
- Foster collaboration between data-driven departments.
- Lead innovation through insight generation.
Conclusion
The Certificate in Data Science (CDS) offers a gateway to a smarter, data-informed future.It goes beyond teaching tools—it cultivates analytical thinking and evidence-based decision-making essential for modern organizations.
This program provides a full-cycle learning journey, from data acquisition to model deployment, all tailored to business needs.Whether you’re in marketing, HR, finance, or oil & gas, this course equips you to better understand your market, improve performance, and make strategic, data-driven decisions.
Good to know
How long is the course, and what are the daily hours?
This date lasts one week: 19 - 23 Jul 2027. A one-week course is 20 hours over 5 days: 4 hours each training day (9am – 1pm). Timing and duration can be customised to your needs.
From the FAQ: What is my daily training agenda?
Which language is the course taught in?
Courses are offered in English and Arabic. The course language is officially English; on request, it can be delivered in Arabic while keeping the English terms.
From the FAQ: In which language do you offer your training courses?
Will I receive a certificate?
Yes. At the end of the course you receive the course certificate issued by BlackBird Training, with an online QR code to verify it.
From the FAQ: Do I receive the certificate at the end of the course?
How do I book, and when do I pay?
Choose Apply now and fill in the form; we guide you through the rest. The acceptance letter is sent within 24 hours of your registration. Payment is due at least 10 days before the course starts, online by credit card or by bank transfer.
From the FAQ: How can I register for a training course in BlackBird?, When do I get my Acceptance Letter?, When do I need to pay?, How can I pay for the course?
Can I cancel or send a colleague instead?
You can send a replacement delegate if you tell us one week before the course starts. Cancellation and refund terms are set out in the cancellation policy.
From the FAQ: Can I send a replacement delegate?
Enquire about this date
Certificate in Data Science (CDS), Paris (France), 19 - 23 Jul 2027