What is the Certified Data Scientist?

The Certified Data Scientist is a globally recognised professional certification by the Global Leadership Institute (GLI), designed to equip professionals with advanced competencies in Soft Skills & Personal Dev..

How long does this certification take?

The programme is 16 Week and can be completed at your own pace through our self-paced online option, or alongside live virtual sessions.

Is this certification globally recognised?

Yes. GLI certifications are internationally recognised and carry CPD credits, making them valuable for career advancement worldwide.

What level is this certification?

This is a Intermediate Level certification, suitable for professionals with relevant experience or background in the field.

You can enrol by emailing info@certifications.ac, contacting us via WhatsApp at +254 722 223 084, or filling the enrolment form below.

Certified Data Scientist in Norway | CDS

Executive Summary

Certified Data Scientist

Designed for today’s high-impact professionals, the Certified Data Scientist (CDS) delivers a rigorous Intermediate-level curriculum that equips participants with the knowledge, tools and frameworks needed to excel in information technology, software, data and digital systems.

This 16 Week programme is structured around ITIL, ISO/IEC and recognised technology and cybersecurity standards, ensuring every graduate applies internationally validated methods to real-world challenges.

GLI’s CDS holders are recognised by leading organisations across Africa, the Gulf, Europe and the Americas as qualified, results-driven professionals. Whether you are advancing your current career or transitioning into new responsibilities, this certification provides the competitive edge you need in 2026 and beyond.

Programme Overview

Certification at a Glance

Certification

Certified Data Scientist

Acronym

CDS

Who Should Enrol?

IT and Systems Professionals
Software Developers and Engineers
Data and Analytics Specialists
IT Managers and Solution Architects

Programme Inclusions

Everything Included in Your Enrolment

All study materials and study guide
Access to GLI online learning portal
Online examination and assessment
Digital certificate and digital badge
Physical certificate (shipped to you)
CPD credits for professional bodies
GLI alumni network membership
Facilitator and tutor support
Resource downloads and reference library
Automatic enrolment confirmation

Certification Benefits

Why This Certification Matters for Your Career

Career Advancement

Accelerate your career towards senior engineering, architecture and IT leadership roles

Professional Recognition

Credential aligned with ITIL, ISO/IEC and recognised technology and cybersecurity standards

Leadership Capability

Develop the strategic and operational skills to lead complex information technology functions

Organisational Impact

Design and implement information technology systems that drive performance and measurable results

Compliance Readiness

Master the standards, compliance and ethical governance central to information technology

Global Employability

Qualify for information technology roles across technology firms, corporates, startups and public institutions worldwide

Competency Framework

Core Competencies You Will Develop

✦Systems, Architecture and Infrastructure

✦Software Development and Application Delivery

✦Data, Analytics and Emerging Technologies

✦Networks, Cloud and Platform Engineering

✦IT Service Management and Governance

✦Professional Ethics and Governance

Course Curriculum

Programme Modules

Click any module to explore the detailed curriculum topics included in this certification.

Foundations and Strategic Context of Certified Data Scientist

Certified Data Scientist: industry context, trends and professional standards
Computing fundamentals and IT concepts
The role of IT in business and value creation
IT operating models and organisation
Hardware, software and systems overview
The technology landscape and trends

Systems, Architecture and Infrastructure

Certified Data Scientist: industry context, trends and professional standards
Systems analysis, design and modelling
Enterprise and solution architecture
Operating systems and virtualisation
Servers, storage and data centres
Cloud computing models (IaaS, PaaS, SaaS)

Data Engineering and Management

Certified Data Scientist: industry context, trends and professional standards
Data modelling and database design
SQL and relational databases
NoSQL and modern data stores
Data warehousing and data lakes
ETL/ELT and data pipelines

Analytics, Machine Learning and AI

Certified Data Scientist: industry context, trends and professional standards
Statistics and exploratory data analysis
Supervised and unsupervised learning
Model training, validation and tuning
Feature engineering and selection
Deep learning and neural networks

Data Visualisation, BI and Decision Support

Certified Data Scientist: industry context, trends and professional standards
Business intelligence and reporting
Dashboards and data storytelling
Visualisation tools and design
KPIs and metric design
Self-service analytics

Cybersecurity and Information Assurance

Certified Data Scientist: industry context, trends and professional standards
Security principles: CIA triad and controls
Threats, vulnerabilities and attacks
Identity and access management
Cryptography and secure communications
Application and network security

Emerging Technologies and Innovation

Certified Data Scientist: industry context, trends and professional standards
Artificial intelligence and machine learning
Generative AI and large language models
Internet of Things (IoT) and edge computing
Blockchain and distributed ledgers
Virtual, augmented and extended reality (XR)

IT Service Management and Operations

Certified Data Scientist: industry context, trends and professional standards
IT service management and ITIL
Service strategy, design and transition
Incident, problem and change management
Service desk and support operations
Availability, capacity and continuity

IT Strategy, Governance and Project Delivery

Certified Data Scientist: industry context, trends and professional standards
IT strategy and business alignment
IT governance frameworks (COBIT)
Enterprise architecture governance
IT project and portfolio management
Vendor, contract and asset management

Stakeholder Engagement and Communication

Certified Data Scientist: industry context, trends and professional standards
Stakeholder mapping and business partnering
Requirements gathering and elicitation
Translating tech to business language
Cross-functional collaboration
Professional and technical documentation

Leading Digital Change and Transformation

Certified Data Scientist: industry context, trends and professional standards
Digital transformation strategy
Change management and adoption
Agile and product operating models
Innovation and experimentation culture
Data-driven and platform business models

Professional Ethics, Standards and Governance

Certified Data Scientist: industry context, trends and professional standards
Professional ethics in technology
Data ethics, privacy and protection
Responsible AI and algorithmic fairness
Intellectual property and licensing
Security, confidentiality and integrity

Performance Measurement and Continuous Improvement

Certified Data Scientist: industry context, trends and professional standards
IT KPIs, SLAs and scorecards
System performance and reliability metrics
Benchmarking against best practice
Quality, defects and reliability
Root-cause analysis and problem solving

Business Analysis and Requirements Engineering

Certified Data Scientist: industry context, trends and professional standards
The business analysis discipline and role
Eliciting and documenting requirements
Process modelling and mapping
User stories, use cases and acceptance criteria
Stakeholder and gap analysis

Advanced Professional Practice: Consulting and Advisory Excellence

Certified Data Scientist: industry context, trends and professional standards
The consulting mindset and trusted advisor positioning
Diagnosing client problems before prescribing solutions
Structuring engagements: scope, deliverables and expectations
Discovery interviews and evidence gathering
Root cause analysis frameworks in advisory work

Data, AI and Digital Tools for the Modern Professional

Certified Data Scientist: industry context, trends and professional standards
Data literacy: reading, questioning and using data
Descriptive statistics for everyday professional decisions
Data visualisation and dashboards that inform
Generative AI as a professional productivity tool
Automation, workflows and no-code tools

Professional Communication, Influence and Negotiation

Certified Data Scientist: industry context, trends and professional standards
Feedback and learner analytics
Active listening and attending
Influencing and negotiation with stakeholders
Offer management, negotiation and pre-boarding
Integrated marketing communications (IMC)

Leadership, People and High-Performance Teams

Certified Data Scientist: industry context, trends and professional standards
Team development and effectiveness
Coaching models and frameworks (GROW)
Cross-functional and matrix teams
Measuring coaching outcomes
Leading through networks

Talent, Culture and the Modern Workplace

Certified Data Scientist: industry context, trends and professional standards
Working with organisations on wellbeing
Wellbeing and the biopsychosocial model
Language and communication training
Belonging, culture and employee resource groups
Team diversity and inclusion

Customer, Market and Stakeholder Value

Certified Data Scientist: industry context, trends and professional standards
Supply markets and the enabling environment
Email marketing and automation
Aligning marketing and sales (smarketing)
Market research design and methods
Data ethics and customer privacy

Financial and Commercial Acumen for Professionals

Certified Data Scientist: industry context, trends and professional standards
Cost of accidents and prevention value
Total cost of ownership
Feasibility, cost and quality analysis
Cybersecurity and financial data protection
Integrity in reporting and investigation

Evidence, Measurement and Decision Quality

Certified Data Scientist: industry context, trends and professional standards
Data, analytics and customer insight
Audit evidence, sampling and testing
Building your professional portfolio and evidence of practice
Record-keeping and data protection
Data literacy: reading, questioning and using data

Strategy, Innovation and Leading Change

Certified Data Scientist: industry context, trends and professional standards
Patrol strategy and response
Category and supplier innovation
Agribusiness models and strategy
Business model design and innovation
Measuring HSE transformation impact

Project and Programme Delivery Essentials

Certified Data Scientist: industry context, trends and professional standards
Designing an intervention or programme
Leading project teams
Security programme design and budgeting
Leading governance projects and change
The project environment and stakeholders

Quality, Process Excellence and Continuous Improvement

Certified Data Scientist: industry context, trends and professional standards
Delivery, quality and stakeholder plan
Quality and delivery metrics
Business process mapping
Time-to-hire, quality-of-hire and cost metrics
Quality, accuracy and error reduction

Governance, Risk, Ethics and Compliance

Certified Data Scientist: industry context, trends and professional standards
Interest-rate risk and gap analysis
Fraud and internal-threat investigation
Business ethics and ethical frameworks
Continuous risk monitoring
Enterprise risk management in banks

Sustainability, Safety and Responsible Practice

Certified Data Scientist: industry context, trends and professional standards
Monitoring, evaluation and sustainability plan
Environmental monitoring
Integrating HSE and environment
Occupational hygiene principles
Environmental impact assessment

Certification Recap and Integrated Review

Your Certification in Action: 90 Days to Recertification

Certified Data Scientist: industry context, trends and professional standards
Designing your first 90 days after certification
Your one-year professional development trajectory
The two-year horizon: expertise, leadership and professional standing
Recertification, CPD and staying current
Building your professional portfolio and evidence of practice

Capstone Project and Certification Readiness

Certified Data Scientist: industry context, trends and professional standards
Capstone scoping: a real technology problem
Requirements and analysis
Designing a technical solution or system
Risk, security and feasibility analysis
Build, test and implementation plan

Learning Outcomes

What You Will Achieve

Establish a comprehensive understanding of Certified Data Scientist principles aligned with ITIL, ISO/IEC and recognised technology and cybersecurity standards
Apply evidence-based methods to improve information technology, software, data and digital systems
Master systems, architecture and infrastructure and software development and application delivery
Apply data, analytics and emerging technologies and networks, cloud and platform engineering in real-world settings
Lead risk management, quality and compliance relevant to your field
Design stakeholder engagement and professional communication strategies
Use data-driven decision-making and performance-measurement tools effectively
Apply internationally recognised best practice to advance your career in information technology

Enrolment Process

How to Get Certified

🎯

Step 1: Choose Your Certification

You are viewing Certified Data Scientist — one of GLI's 1,990+ globally recognised professional certifications.

💳

Step 2: Enrol & Pay Online — Instantly

Click Enrol & Study Online to register and pay securely via Paystack, Visa, Mastercard, M-Pesa or bank transfer. Access is granted the moment payment is confirmed.

📚

Step 3: Study in the GLI Learning Portal

Work through 15 structured modules and 150 lessons at your own pace, with downloadable resources and expert-designed content — all inside the LMS.

🎓

Step 4: Pass, Get Certified & Verified

Sit your final examination online, earn your certificate instantly, and receive a globally verifiable Certificate ID — plus GLI Alumni Network access.

🎓 Enrol & Study Online — Instant Access

Secure checkout · Instant LMS access · Globally verifiable certificate

Frequently Asked Questions

Common Questions

What is the CDS certification?

The Certified Data Scientist (CDS) is a Intermediate-level professional certification awarded by the Global Leadership Institute (GLI). It is designed to equip professionals in information technology, software, data and digital systems with practical skills, internationally recognised frameworks, and the credentials needed to advance their careers.

Who should enrol in the CDS?

This certification is ideal for IT and Systems Professionals, Software Developers and Engineers, Data and Analytics Specialists and IT Managers and Solution Architects, and other professionals seeking to formalise their expertise in information technology, software, data and digital systems with a globally recognised credential.

How long does the CDS certification take to complete?

The programme is structured over 16 Week and offers flexible learning modes. Self-paced learners can progress at their own schedule, while live virtual participants follow a structured cohort schedule with facilitator-led sessions.

Is the CDS internationally recognised?

Yes. GLI certifications are recognised across 85+ countries and are aligned with ITIL, ISO/IEC and recognised technology and cybersecurity standards. Graduates receive a digital certificate, a physical certificate and CPD credits recognised by employers worldwide.

What is the cost of the CDS certification?

The Certified Data Scientist is offered in two formats: Self-Paced at USD 349 and Live Virtual at USD 549. Corporate group rates are available for organisations enrolling 5 or more participants. Contact GLI for a bespoke corporate training quotation.

What does the CDS certification include?

Enrolment includes all study materials and study guides, access to GLI's online learning portal, online examination, digital certificate and badge, physical certificate (posted), CPD credits, GLI alumni network membership, and ongoing facilitator support.

What is the assessment format for the CDS?

The Certified Data Scientist is assessed through an online examination consisting of multiple-choice questions, case study analysis, and practical application assignments. The assessment is designed to evaluate real-world competency, not just theoretical recall.

What CPD credits do I earn from the CDS?

The Certified Data Scientist carries Continuing Professional Development (CPD) credits, which can be applied towards professional body requirements including recognised international professional associations.

Can I study the CDS while working full-time?

Absolutely. The self-paced option is designed for busy working professionals and allows you to study when and where it suits you. Live virtual sessions are typically scheduled in the evenings or on weekends to accommodate professional commitments.

What career outcomes can I expect from the CDS?

Graduates progress towards senior engineering, architecture and IT leadership roles. The CDS strengthens your expertise in information technology, software, data and digital systems and positions you for advancement across technology firms, corporates, startups and public institutions.

Certified Data Scientist

Certified Data Scientist

Certification at a Glance

Who Should Enrol?

Everything Included in Your Enrolment

Why This Certification Matters for Your Career

Core Competencies You Will Develop

Programme Modules

What You Will Achieve

How to Get Certified

Common Questions

What Our Alumni Say

You May Also Like

Certified Adult Learning Specialist

Certified Quality Process Analyst

Certified Goal Setting Coach

Certified Learning & Development Specialist

Certified IoT Solutions Architect

Certified Professional in Supplier Diversity