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Professional Diploma in Data Analytics

 

Data Science and Information Technology / Data Analytics — Novera University

 

1. Program Overview:

An accredited professional and applied program extending over 3 months (80 hours of approved study load), aimed at preparing and qualifying professional data analysts capable of collecting, processing, and analyzing data and transforming it into strategic insights that support intelligent decision-making in organizations. The program covers the complete data lifecycle, Advanced Excel techniques, management and querying of relational databases using SQL, building interactive dashboards through Power BI, applied statistics and hypothesis testing, Python programming for data analysis, an introduction to Big Data, and data governance and ethics.

2. Key Objectives:

  •         Understanding the data lifecycle and its tools: understanding descriptive, diagnostic, predictive, and prescriptive analytical approaches and the stages of data processing from collection to presentation.
  •         Mastering advanced analysis and querying tools: cleaning and processing data using advanced functions and PivotTables in Excel, and writing complex SQL queries (JOINs, GROUP BY) to work with databases.
  •         Data visualization and dashboard development: designing dynamic and interactive reports and dashboards using Power BI and Python libraries to support decision-makers.
  •         Statistical and programming analysis and governance: applying statistical concepts for hypothesis testing and regression models, using Python libraries (Pandas, Matplotlib, Seaborn), and applying data privacy and governance standards.

3. Target Audience:

  •         Data analysts, Business Analysts, and Business Intelligence specialists (BI Specialists).
  •         Employees and professionals seeking a career transition into the field of data science and analytics.
  •         Administrators, decision-makers, and project managers seeking to lead their organizations through data-driven decisions.
  •         Graduates and students of Information Technology, Computer Science, Engineering, Economics, and Statistics.

4. Study Plan and Courses (8 Courses — 24 Interactive Lectures):

Course Code

Course Title

Number of Lectures

Total Hours

 

DAT101

Introduction to Data Analytics and the Data Lifecycle

3

6 hours

DAT102

Advanced Excel and Data Analysis

3

6 hours

DAT103

SQL and Databases

3

6 hours

DAT104

Data Visualization and Power BI

3

6 hours

DAT105

Applied Statistics for Data Analysis

3

6 hours

DAT106

Introduction to Python for Data Analysis

3

6 hours

DAT107

Big Data Analytics and Data-Driven Decision-Making

3

6 hours

DAT108

Data Ethics and Governance

3

6 hours

Total

8 Courses

24 Lectures

48 Training Hours

 

5. Organizational Structure and Assessment System:

  •         Duration and sessions: 3 months (evening period), at a rate of two lectures per week, two hours per lecture = 48 interactive training hours.
  •         Language of study and delivery method: Arabic and English | fully remote interactive training (Online).
  •         Distribution of credit hours (80 hours):

·         48 hours: live interactive lectures.

·         20 hours: required readings and open resources.

·         8 hours: chapter questions and self-assessment.

·         4 hours: final review and graduation project.

  •         Attendance and assessment requirements: attendance of no less than 75% of the lectures, and completion of periodic analytical projects and assignments.

  •         Certificate and graduation project: the graduate is awarded a Professional Diploma in Data Analytics after completing an integrated practical project that includes analyzing a real dataset, preparing a report and an interactive dashboard, and passing the online examination.

 

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