Program Overview
- Vocational Data science Career Pathway Program that takes a learner from a Data Analyst to a Data Scientist role
- Data Analyst: Enables business to maximize the value of their data assets by using Microsoft Power BI. As a subject matter expert, Data Analyst is responsible for designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value through easy-to-comprehend data visualizations
- Data Scientist: Applies their knowledge of data science and machine learning to implement and run machine learning workloads in the cloud, in particular, using Azure Machine Learning Services. This entails planning and creating a suitable working environment for data science workloads on Azure, running data experiments and training predictive models, and deploying machine learning models into production
- Focused on the following job skills:
- Data Insights & Data Preparation
- Data Engineering & Machine Learning
- Program Level: Beginner to Intermediate Level
Program Length: 400 hours
Certifications: Four vouchers are made available for learners towards certifications listed below.
- Microsoft Azure Data Fundamentals (DP-900)
- Microsoft Power Platform Fundamentals (PL-900)
- Analyzing Data with Power BI (DA-100)
- Microsoft Azure Fundamentals (AZ-900)
- Designing and Implementing a Data Science Solution on Azure (DP-100)
Target Audience:
- Recent graduates and transitioning career professionals seeking to enter the field of Data science starting with Data/Business Analytics
- Software Developers looking to transform their skills towards Model Development
- Analytics professionals seeking to understand the world of Data Engineering and Applied Machine Learning
Roles:
Database Developer
Software Engineer
Database Administrator
Report Visualizer
Power BI Administrator
Power BI Architect
Data Visualization Engineer
Power Query Developer
Cloud Engineer
Data Scientist
PROGRAM DETAIL
Modeling for Insights (120 hours): this module focuses on developing a well-rounded technical foundation which includes hands-on Microsoft Excel, Structured Query Language (SQL), and communications through Analysis and Visualization.
- Data Modeling Context & Applied Excel (40 hours)
- Structured Query Language (SQL) Queries
- Data Analysis and Visualization with Power BI
Modeling for Prediction (120 hours): Automation is the significant aspect of this module with emphasis on Data Modeling using real-world examples that helps look at the reports in a different way i.e., with the correct model, the correct answer is always a simpler one.
- Data Modeling with DAX (Data Analysis Expressions)
- Data Preparation & Data Shaping with Power Query
- Enterprise Business Process Automation with Power Automate
Scaling for Analytics (120 hours): Data Engineering Essentials is the focus here - Python, Machine Learning and Spark SQL. Scaling Analytics through the Auto ML - apply regression and classification techniques to power business forecasts and drive decision-making and strategy,
- Python for Data Analysis
- Machine Learning with Azure ML
- Data Engineering with Spark SQL
Capstone Project (40 hours): This module serves as the capstone for the 9 weeks of learning through integration of Data Science skills through a project focused on real-world open data. The learner may choose to work alone but preferably in a group of 2-3. In addition, support from staff is provided to tailor the data science process steps to develop a minimum viable data product. A learner is assessed on their problem hypothesis, statistical model, insights delivered through use of the model, flexibility of the model. The goal of this this module is to help a learner to develop an effective LinkedIn Profile, showcase project portfolio, prepare for interviews by revisiting their capstone problem, and share capstone project results.