Python for Data Science for Managers and Supervisors
Sharjah Publishing City Free Zone, Sharjah, United Arab Emirates
Course Overview
Python for Data Science for Managers and Supervisors is an intensive, practice-oriented programme designed by Qimma Training for professionals in IT, AI & Digital Transformation. It focuses on the managerial, decision-making and supervisory side of Python for Data Science, helping leaders plan, control and continuously improve performance, equipping participants with the knowledge, tools and confidence to deliver measurable results.
The course runs over 5 or 10 days in classroom sessions across Europe and the Middle East, live online, or in-house at your premises. It blends expert-led instruction, real case studies, group workshops and practical exercises, and every in-house edition can be fully customised to your industry, assets, procedures and competency framework.
Learning Objectives
By the end of this course, participants will be able to:
- Explain the core concepts, terminology and principles of Python for Data Science
- Apply relevant international standards, codes and recognised best practices
- Use practical tools and techniques to analyse problems and make sound decisions
- Identify risks, gaps and improvement opportunities in current practice
- Measure performance with meaningful KPIs and benchmarks
- Build a practical action plan to implement Python for Data Science improvements in the workplace
- Lead teams, allocate resources and manage stakeholders effectively
Who Should Attend
IT managers, digital transformation leads, data and AI professionals, cybersecurity staff and business leaders driving digital change.
Designed for managers, supervisors, team leaders and decision-makers.
Course Outline
Day 1Introduction and Fundamentals
- Scope, objectives and key terminology of Python for Data Science
- The role of Python for Data Science in organisational performance
- Relevant international standards and frameworks
- Pre-course assessment and learning goals
Day 2Core Principles and Methodologies
- Main methods, models and approaches
- Roles, responsibilities and interfaces
- Common challenges and how to overcome them
- Group exercise: diagnosing current practice
Day 3Tools, Techniques and Best Practices
- Practical tools, templates and checklists
- Data collection, analysis and interpretation
- Benchmarking against international best practice
- Workshop: applying the tools to a real case
Day 4Practical Application and Case Studies
- Case studies from IT, AI & Digital Transformation
- Risk, compliance and quality considerations
- Digital tools and emerging trends
- Team simulation and role-play
Day 5Performance, Improvement and Action Planning
- KPIs and performance measurement
- Continuous improvement and sustainability of results
- Building a personal and organisational action plan
- Post-course assessment, review and certificates
Day 1Introduction and Fundamentals
- Scope, objectives and key terminology of Python for Data Science
- The role of Python for Data Science in organisational performance
- Relevant international standards and frameworks
- Pre-course assessment and learning goals
Day 2Core Principles and Methodologies
- Main methods, models and approaches
- Roles, responsibilities and interfaces
- Common challenges and how to overcome them
- Group exercise: diagnosing current practice
Day 3Tools, Techniques and Best Practices
- Practical tools, templates and checklists
- Data collection, analysis and interpretation
- Benchmarking against international best practice
- Workshop: applying the tools to a real case
Day 4Practical Application and Case Studies
- Case studies from IT, AI & Digital Transformation
- Risk, compliance and quality considerations
- Digital tools and emerging trends
- Team simulation and role-play
Day 5Performance, Improvement and Action Planning
- KPIs and performance measurement
- Continuous improvement and sustainability of results
- Building a personal and organisational action plan
- Post-course assessment, review and certificates
Day 6Advanced Concepts and Analysis
- Advanced analytical techniques for Python for Data Science
- Interpreting complex data and scenarios
- Lessons learned from major global cases
Day 7Digital Transformation and Emerging Technologies
- Automation, AI and analytics applied to Python for Data Science
- Selecting and implementing digital solutions
- Future trends to 2030
Day 8Integrated Workshop and Simulation
- Multi-disciplinary simulation exercise
- Decision-making under time and cost constraints
- Debrief and peer feedback
Day 9Leadership, Change and Implementation
- Building the business case and securing buy-in
- Managing change and organisational culture
- Governance, audits and reporting
Day 10Capstone Project and Final Assessment
- Capstone project presentations
- Expert review and feedback
- Final assessment and certification
Training Methodology
Interactive lectures, real-world case studies, group discussions, practical workshops, simulations and pre/post assessments. Participants receive a full set of course materials and templates they can use back at work.
Certificate
Participants who complete the course receive a Qimma Training Certificate of Completion stating the course title, code, duration and training hours (30 hours for 5 days / 60 hours for 10 days).
Fees & Formats
| Format | 5 days | 10 days |
|---|---|---|
| Classroom | $5,750 | $9,900 |
| Live Online | $3,000 | $5,750 |
| In-House | On request — customised to your organisation | |
Fees are per participant in US dollars. In-house programmes are quoted per group and can be fully customised.
Upcoming Sessions 2027 – 2030
| Dates | City | Duration | Fee | |
|---|---|---|---|---|
| 2027 | ||||
| 12 Apr – 16 Apr 2027 | Marrakech | 5 days | $5,750 | Register |
| 11 Jul – 15 Jul 2027 | Amman | 5 days | $5,750 | Register |
| 18 Oct – 22 Oct 2027 | Live Online | 5 days | $3,000 | Register |
| 2028 | ||||
| 13 Mar – 24 Mar 2028 | Geneva | 10 days | $9,900 | Register |
| 14 Aug – 18 Aug 2028 | Berlin | 5 days | $5,750 | Register |
| 6 Nov – 17 Nov 2028 | Live Online | 10 days | $5,750 | Register |
| 2029 | ||||
| 12 Feb – 16 Feb 2029 | Istanbul | 5 days | $5,750 | Register |
| 20 Aug – 24 Aug 2029 | Berlin | 5 days | $5,750 | Register |
| 12 Nov – 16 Nov 2029 | Live Online | 5 days | $3,000 | Register |
| 2030 | ||||
| 11 Feb – 15 Feb 2030 | Brussels | 5 days | $5,750 | Register |
| 6 May – 10 May 2030 | Munich | 5 days | $5,750 | Register |
| 18 Nov – 22 Nov 2030 | Live Online | 5 days | $3,000 | Register |