Specialization Certificate in Data Analytics
Specialization Certificate Program
The Professional Certificate in Data Analytics is designed to equip learners with practical skills in data collection, processing, analysis, visualization, and business decision-making. The program combines analytical concepts with industry-standard tools such as SQL, Tableau, spreadsheets, and Generative AI technologies. Through hands-on exercises, case studies, and a capstone project, learners develop the ability to transform raw data into meaningful insights that support organizational growth and strategic planning across multiple industries.
Duration
250+ hours
5 Months @ 15 hours per week
Session Days
Weekdays
Weekends
Course Delivery
Classroom
Live Remote
Target Audience
Students, Professionals
Level
Foundation to Intermediate
Cost
USD 99 per month
PKR 30,000 per month
* Installments options are available
Program Features
Data Analytics has become one of the most important domains in the digital economy. Organizations across healthcare, banking, retail, education, manufacturing, logistics, and government rely on data-driven insights for informed decision-making. Skilled data analysts help organizations improve efficiency, identify market trends, understand customer behavior, reduce operational costs, and enhance business performance. With the rapid growth of big data and artificial intelligence, professionals with analytical and visualization skills are increasingly in demand worldwide.
Why to Study This Program?
Skills Learners Will Gain
Program Learning Outcomes
By the end of the program, learners will be able to:
Target Job Roles
Curriculum
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Introduction to Data Analytics ▸ Role of Data Analyst ▸ Introduction to Business Analytics ▸ Excel for Analytics ▸ Conditional Formatting & Functions ▸ Analysis with Pivot Tables ▸ Statistical Data Analysis ▸ Dashboard Creation ▸ Introduction to Power BI ▸ Data Visualization Principles | ▸ Analytics lifecycle activity ▸ Case study analysis ▸ Business KPI exercises ▸ Spreadsheet reporting labs ▸ Formula-based assignments ▸ Sales data reporting ▸ Statistical calculations ▸ Dashboard development ▸ Data import and modeling ▸ Visualization redesign tasks | ▸ Google Sheets ▸ Power BI ▸ MS Excel |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Fundamental SQL Statements ▸ Database Backup & Restore ▸ Filtering & Ordering ▸ Joins ▸ Subqueries ▸ Views & Indexes | ▸ Query writing labs ▸ Backup simulations ▸ Data retrieval exercises ▸ Multi-table reporting ▸ Nested query labs ▸ Query optimization tasks | ▸ MySQL ▸ SQL Server ▸ PostgreSQL |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Data Collection ▸ Data Preparation ▸ Statistical Summaries ▸ Exploratory Data Analysis (EDA) ▸ Descriptive Statistics ▸ Measures of Central Tendency ▸ Measures of Dispersion ▸ Percentiles and Quartiles ▸ Trend Analysis ▸ Dashboard Reporting ▸ Communicating Insights through Visuals | ▸ Dataset acquisition activities ▸ Cleaning exercises ▸ Reporting labs ▸ Visualization and summaries ▸ Sales trend analysis ▸ KPI dashboard creation | ▸ Excel ▸ Python ▸ pandas ▸ Power BI ▸ Tableau |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Root Cause Analysis ▸ Probability Theory ▸ Sampling Techniques ▸ Hypothesis Testing ▸ Correlation & Causation ▸ Regression Analysis ▸ Anomaly Detection ▸ Comparative Analysis Techniques ▸ Data Interpretation and Insight Generation | ▸ Problem investigation labs ▸ Probability simulations ▸ Sampling exercises ▸ Statistical testing labs ▸ Correlation analysis ▸ Regression modeling ▸ Fraud detection case study | ▸ Excel ▸ Python ▸ SciPy ▸ pandas ▸ scikit-learn |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Tableau Fundamentals ▸ Data Organization ▸ Charts & Dashboards ▸ Filters & Parameters ▸ Heat Maps, Treemaps & Pareto Charts ▸ Designing Interactive Dashboards ▸ Storytelling with Data ▸ Dashboard Publishing ▸ Visualization Best Practices | ▸ Dashboard setup ▸ Dataset preparation ▸ Visualization labs ▸ Interactive reports ▸ Advanced visualization tasks ▸ Storyboard presentation ▸ Dashboard deployment | ▸ Tableau |
| Topics | Practical Work | Tools & Technologies |
|---|---|---|
| ▸ Generative AI Basics ▸ AI in Analytics ▸ Neural Networks & GANs ▸ Transformers & LLMs ▸ Prompt Engineering ▸ Data Augmentation ▸ AI-Based Visualization ▸ AI in ETL ▸ AI Forecasting ▸ Future of AI Analytics | ▸ AI demonstrations ▸ AI workflow case studies ▸ AI model visualization ▸ Chatbot interaction labs ▸ Prompt creation exercises ▸ Synthetic data generation ▸ Visualization automation ▸ Intelligent transformation tasks ▸ Predictive analytics enhancement ▸ Industry trend analysis | ▸ ChatGPT ▸ Python ▸ ChatGPT ▸ TensorFlow ▸ Hugging Face ▸ OpenAI Playground ▸ Python ▸ Power BI AI ▸ Python ▸ AutoML ▸ Research Platforms |
| Project Activities | Deliverables | Tools & Technologies |
|---|---|---|
| ▸ Industry-oriented project ▸ Data collection & preparation ▸ Analytics & visualization ▸ Predictive modeling ▸ Final presentation | ▸ Project proposal ▸ Dataset and ETL workflow ▸ Dashboard and reports ▸ ML models ▸ Report and presentation | ▸ Any relevant tools ▸ Python, SQL ▸ Power BI, Tableau ▸ scikit-learn ▸ PowerPoint |