Data Analyst Program

Specifically designed for students with no experience to land a role in less than 6 weeks.

Job Opportunities after this course

Data Analyst

Other titles you may find on job sites with similar responsibilities: Business Analyst,Data Scientist,Data Engineer,....

Niche: Marketing, Financce, Logistic, Business and so on...

Expected Salary for this role: $80k–100k plus super (as of 2024)

Course Structure

The course will be broken down into 3 simple training steps:

Step 1: Deep Knowledge Training

Data Analysis

1. Introduction to Data Analysis: Covers foundational concepts, including understanding different types of data, data collection methods, and basic data cleaning techniques. Introduces statistical measures and how to derive meaningful insights from datasets.

2. Statistics: Focuses on statistical methods crucial for analysing data, including probability distributions, hypothesis testing, regression analysis, and statistical inference, enabling analysts to make data-driven decisions.

3. Data Wrangling: Teaches techniques for cleaning, structuring, and enriching raw data into a desired format for easier access and analysis. Includes handling missing values, data transformation, and combining datasets.

4. Data Visualisation with Python: Involves learning to use Python libraries like Matplotlib, Seaborn, and Plotly for creating informative and interactive visualisations to represent complex data insights visually.

SQL and Databases

SQL (SQL Server, MySQL, Postgres, Oracle DB): Comprehensive training on SQL syntax and advanced queries to manage and retrieve data efficiently from various database systems. Covers database design, indexing, joins, and stored procedures.

Advanced Data Visualisation

• Tableau, PowerBI: Focuses on using these tools for creating dynamic and interactive data visualisations to help businesses understand their data and make informed decisions.

• Data Storytelling: Teaches the art of crafting compelling narratives around data findings to effectively communicate insights to non-technical stakeholders.

• Advanced Data Storytelling: Builds on basic storytelling techniques with advanced strategies for engaging audiences, using storytelling frameworks, and leveraging visualisations to support the narrative.

Excel, Business, and BI Analytics

• Advanced Excel for Data Analysis: Advanced functions, pivot tables, macros, and VBA scripting to automate tasks and analyse data.

• Business Analytics using SQL: Applies SQL skills to solve business problems, focusing on queries that extract insights from business data.

• BI Analytics: Covers the end-to-end process of data analysis, including data preparation, modelling, and predictive analysis to support business intelligence efforts.

Financial and Marketing Analytics

• Financial Analytics: Involves analysing financial data to forecast future financial performance, manage risk, and evaluate financial instruments. Includes Excel modelling and analysis of financial statements.

• Marketing Analytics: Techniques for analysing market data to identify trends, measure campaign effectiveness, and make data-driven marketing decisions.

Data Tools, Cloud, and Programming

Data Tools & Cloud (AWS, Azure, Snowflakes, Databricks, Apache Airflow, FiveTran, Data Build Tools): Training on using cloud services and data engineering tools for data storage, processing, and analysis at scale.

Programming Languages (Python, R, SQL): Developing proficiency in these key languages for data analysis, statistical computing, and database management.

Step 2: Practical Application

Commercial Projects

Participants engage in real-world projects, applying the skills learned to solve business problems. This includes data collection, analysis, visualisation, and presenting findings.

Step 3: Career Preparation

Mock Interviews/Technical Tests

Tailored training for job interviews, focusing on technical skills and problem-solving. Includes practising with common interview questions and receiving feedback to improve performance.

In short: these elaborations provide a deeper understanding of what each component of the training program entails, aimed at equipping individuals with the necessary skills to excel in the field of data analysis.