Diploma in Data Analytics Professional drafted

Program Overview

This 10-month Diploma in Data Analytics program equips individuals with the skills and knowledge to become proficient data analysts. The program prepares graduates for success in data analyst roles with the skills required for effective data analysis, visualization, and interpretation.

Program Outline

Diploma in Data Analytics (Analytics Pro) Training Program for Data Analysts

Degree Overview:

• Provide a comprehensive understanding of statistical analysis, probability theory, and data science fundamentals using Python.
• Train individuals to transform and gain valuable insights from data, creating meaningful visualizations and making informed predictions based on their findings.
• Prepare graduates for success in data analyst roles with the skills required for effective data analysis, visualization, and interpretation.

Program Description:

• The course curriculum offers a blend of theoretical and practical training, emphasizing hands-on experience through real-world data sets and industry-relevant case studies.
• The program is designed for working professionals and offers flexibility with evening classes held twice weekly (6.30 pm to 9.30 pm) on Tuesdays and Thursdays.

Outline:

Program Content and Structure:

• The curriculum is structured in four stages, progressively building participant knowledge and expertise in data analysis.
• Each stage focuses on distinct areas, with Stage 1 covering SQL Database structures, Stage 2 concentrating on Python Programming, Stage 3 delving into Data Analysis and Visualization, and Stage 4 exploring Big Data and Cloud computing.
• Participants complete four individual tests after each stage and undertake an ongoing project throughout the duration of the course, contributing significantly to the final grade.
• Assessment is divided between individual tests (40% contribution) and the ongoing project (60% contribution).

Course Schedule:

The in-depth Diploma in Data Analytics curriculum includes:

• Stage 1 - SQL & Databases (125 Hours):
• Module 1 - Basic data analysis using SQL (50 Hours): Covering fundamental concepts, statement writing, data filtering and sorting, scalar and group functions, joins, data modification and creation, and more.
• Stage 2 - Python Programming (50 Hours):
• Stage 3 - Data Analysis and Visualization (130 Hours):
• Module 2 - Data analysis using Pandas (25 Hours): Mastering filtering and sorting operations with scalar and group functions, exploring set and join operations, modifying schema and using Pandas indexes, utilizing pivot operations and working with input/output data sets, employing analytical functions, performing interactive analysis and basic machine learning tasks.
• Module 4 - Business Intelligence and Data visualization with Power BI (50 Hours): Introduction to Power BI concepts and architecture, building insightful visualizations with Power BI development, integrating Power BI with Python, working with data security, sharing and deployment functionalities.
• Stage 4 - Big Data and Cloud (40 Hours):
• Module 2 - Hadoop Basics: Exploring the core principles and architecture of Hadoop.
• Module 7 - Use Cases: Exploring various applications of big data technology in different industries and scenarios.

Assessment:

Assessment Methods and Criteria:

• Individual Tests (4 stages, each contributing 10% to final grade): Assessing knowledge acquisition and understanding through written examinations after each of the program's four stages.
• Ongoing Project (contributes 60% towards the overall grade): Evaluating participants' practical ability to apply learned skills and solve real-world problems through an in-depth, sustained project that runs throughout the entire program.

Teaching:

Teaching Methods:

• Interactive and practical learning through real-world examples, datasets, and industry-relevant case studies to aid in knowledge application and interpretation.
• Emphasis on hands-on experience through individual and collaborative project work.

Faculty:

Experienced and industry-connected instructors.

Unique Approach:

• Blended learning model combining face-to-face classroom instruction and live, virtual interactions via interactive online learning platforms, providing an accessible and engaging educational environment amidst a global landscape.
• Interactive sessions with expert tutors, enabling individual guidance, mentorship, and direct engagement.

Careers:

Career Opportunities:

• Data Analyst Roles: Equipping graduates with the necessary expertise to pursue a wide range of data analyst positions across various industries.
• Emerging Market Fit: Addressing the growing demand for skilled data analysts, with a projected 20% industry growth by 2028 (as per U.S. Bureau of Labor Statistics).

Potential Industries and Employers:

• ICT (e.g., Google, eBay, Facebook, Amazon, Paddy Power)
• Pharmaceutical (e.g., Jansen, Merck, GSK)
• Financial services (e.g., Bank of Ireland, AXA, EY, Accenture, Deloitte)

Other:

• Digital Certificate and Badge
• Flexible Learning: Balancing work with academics, the course provides adaptable options for payment, catering to individual circumstances.