75-hour intensive Data Analytics training program
Globally recognised Data Science certification
Copilot & Automation Sandbox system exposure
Flexible on-site & live virtual options
Monthly instalment payment plans
What our training includes
Upcoming sessions
Python basics
Pandas and NumPy
Data manipulation
Visualization libraries
Analysis workflows
Generate Python scripts and debug code
Descriptive statistics
Inferential statistics
Hypothesis testing
Regression analysis
Business applications
Generate statistical interpretations
ML concepts
Supervised vs unsupervised learning
Model building
Evaluation metrics
Applications
Suggest algorithms and model logic
AI vs ML
Predictive analytics
Automation
AI applications
Business use cases
Generate AI use cases and workflows
Time-series analysis
Forecasting models
Trend analysis
Demand prediction
Business forecasting
Generate forecasting insights
Data storytelling
Visualization best practices
Communication techniques
Business presentations
Stakeholder reporting
Generate summaries and narratives
Participants will build and present a comprehensive data analytics solution using Excel, SQL, Python, and Power BI to
The Automation Sandbox enables participants to apply the knowledge gained during the training to their own professional responsibilities and everyday work processes.
This activity encourages participants to examine their existing workflows and consider how the concepts learned in the program can be used to improve efficiency, streamline tasks, and support better operational outcomes.
Through guided exercises, participants will review and analyze their current workflows, identifying opportunities for improvement through clearer structuring, simplification, and logical sequencing of tasks. They will then translate their process expertise into well-defined workflow structures that outline key steps, decision points, and expected results.
These structured workflows are designed to be easily understood by technical automation teams, enabling effective implementation while bridging the gap between operational process knowledge and technical automation development.
Time-series analysis
Forecasting models
Trend analysis
Demand prediction
Business forecasting
Generate forecasting insights
Data storytelling
Visualization best practices
Communication techniques
Business presentations
Stakeholder reporting
Generate summaries and narratives
Participants will build and present a comprehensive data analytics solution using Excel, SQL, Python, and Power BI to
The Automation Sandbox enables participants to apply the knowledge gained during the training to their own professional responsibilities and everyday work processes.
This activity encourages participants to examine their existing workflows and consider how the concepts learned in the program can be used to improve efficiency, streamline tasks, and support better operational outcomes. It helps participants approach their processes from an automation-oriented perspective, identifying areas where structured processes and automation could add value while also recognizing situations where automation may not be appropriate.
Through guided exercises, participants will review and analyze their current workflows, identifying opportunities for improvement through clearer structuring, simplification, and logical sequencing of tasks. They will then translate their process expertise into well-defined workflow structures that outline key steps, decision points, and expected results.
These structured workflows are designed to be easily understood by technical automation teams, enabling effective implementation while bridging the gap between operational process knowledge and technical automation development.
Successful completion of our training will help professionals in the following ways:
1
Explain the analytics lifecycle and translate business questions into measurable metrics and KPIs
2
Prepare analysis-ready datasets using cleaning, transformation, and normalisation methods for reliable outputs
3
Create stakeholder-focused dashboards and communicate insights using effective data storytelling practices
4
Apply statistical analysis, hypothesis testing, and regression concepts to support evidence-based decisions
5
Build foundational machine learning, AI analytics, and forecasting capability for prediction and planning scenarios
Overall ratings by our students
Our Data Analytics and Data Science course in Dubai is a practical certification that trains you to work through an analytics project the way organizations do. You start by understanding how analytics creates business impact, then practise Excel-based analysis and data preparation.
This program moves into Power BI dashboards and storytelling, builds SQL skills for extracting accurate datasets, and introduces Python for analysis tasks. It also covers statistics, regression, machine learning fundamentals, AI use cases, and time series forecasting, concluding with an industry simulation presentation.
Dubai organizations often rely on Excel and Power BI for reporting and stakeholder dashboards. This course strengthens reporting capability first, then adds SQL for extracting reliable datasets and Python for data cleaning and analysis tasks to support deeper business insights.
The Data Analytics and Data Science course in Dubai aligns with tasks expected in Data Analyst and BI roles in the UAE, These include cleaning files, preparing reliable datasets, combining data during preprocessing, writing join queries, and building interactive Power BI dashboards for stakeholder reporting.
Participants learn predictive thinking through statistics, regression, machine learning fundamentals, and forecasting. This supports more forward-looking analysis in planning, performance tracking, and decision-support reporting.
During the Data Analytics and Data Science training in Dubai, you will produce:
1. Cleaned datasets with missing values and outliers addressed
2. Transformed and normalised data prepared for analysis
3. SQL query outputs and summary reports from sample databases
4. Power BI dashboards with operational KPIs and interactive visuals
5. Python analysis outputs using NumPy and Pandas with basic charts
6. Final industry simulation presentation with business recommendations
In a Dubai business setting, the Data Analytics and Data Science course helps you apply AI concepts within structured analytics workflows. You first build practical foundations in Excel, SQL, Power BI, and Python, then progress into AI in business analytics, including predictive analytics and automation use cases.
The training keeps a strong focus on data reliability, with hands-on preprocessing, validation practices, and clear reporting, so insights remain accurate, business-ready, and aligned with decision-making needs.
Learners Point ensures you leave with workplace-ready outputs, not just tool familiarity. Our course uses a running industry simulation that connects Excel analysis, preprocessing, Power BI dashboards, SQL extraction, and Python workflows into one business storyline.
You also apply statistics, regression, machine learning fundamentals, AI concepts, and forecasting to support evidence-based decisions. We end this training with a stakeholder-style presentation built on real deliverables.
Copilot integration and the Automation Sandbox make this course more practical and workplace-focused for professionals in Dubai. Copilot is used across the program to support tasks such as summarising datasets, generating draft SQL and Python logic, explaining analytical steps, assisting with debugging, suggesting dashboard ideas, and refining business presentations.
The Automation Sandbox strengthens this learning by helping participants apply course concepts to their own day-to-day responsibilities. Through guided exercises, they review existing workflows, identify opportunities to improve efficiency, and organise tasks in a clearer, more automation-ready way.
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