Data Analysis

Apply Now
Delivery Mode Face to face/Online/Hybrid
Pricing $3500

Highlights of Data Analysis course

  • Expert Instructors from Top Companies All instructors at Career Master are seasoned data analysts and data scientists with diverse industry backgrounds. They provide professional knowledge and share insights on the application of data analysis across various industries, helping students become highly sought-after analysts in the job market.

  • Structured Milestones for Systematic Learning: The course is structured around key milestones in data analysis projects:
    • Project Proposal: Understand project background and client requirements, analyze potential needs and directions.
    • Data Exploration & Data Cleaning: Optimize data queries and structure using SQL, connect to AWS, and perform simple analysis with SQL.
    • Data Visualization: Use Power BI for basic visualization of processed data.
    • Machine Learning & Modeling: Conduct deep analysis and model selection with Python and Pandas.
  • Milestone Checklists for Targeted Learning Instructors provide detailed milestone checklists outlining the specific knowledge and skills students need at each stage. Students can use these checklists to focus their learning and ensure they have mastered each area effectively.

  • Comprehensive “Analysis + Technical Skills” Training In addition to industry-standard tools and techniques to enhance job competitiveness, the course includes case studies, storytelling, A/B testing, and real-world applications to build analytical skills. It also covers statistical theory and practical application, fostering a strong analytical mindset.The course encompasses all essential skills for data analysis roles, including both technical and soft skills, such as analytical and communication abilities. Alongside regular live classes, there are occasional tutorials to accelerate knowledge comprehension. The course includes the following components:
    • Practical Statistics Knowledge: Covers essential statistical concepts, like A/B Testing and Hypothesis Testing, using numerous real-world cases.
    • Core Tools (SQL & Python): Instructors focus on essential skills in SQL and Python for business analysis, with ample classic case studies to practice.
    • Tableau for Data Visualization: From installation to creating professional dashboards, covering both basic and advanced topics.
    • Power BI: A robust business intelligence tool by Microsoft for data visualization, analysis, and reporting, used with real-world cases to enhance learning and practical application.
    • Machine Learning Algorithms: While machine learning isn’t mandatory for data analysis, understanding it can boost career growth. This course includes all essential machine learning knowledge for analysts.
    • Advanced Excel & VBA: Essential skills for financial analysts, especially for those from accounting or finance backgrounds.
  • Team Project Presentation to Industry ExpertsAt the end of the course, students will present their projects to instructors, tutors, and industry experts. This is an opportunity to showcase their work to professionals, receive valuable feedback, gain industry insights, and possibly obtain job referrals.

Why Become a Data Analyst?

  • High Demand: As businesses continue to focus on digital transformation and data-driven decisions, the demand for data analysts in Australia is growing rapidly. Key industries like retail, financial services, and healthcare are actively seeking professionals with the skills to analyze large datasets and extract actionable insights. This demand is expected to persist as organizations increasingly rely on big data for decision-making.
  • Attractive Salary: Data analysts in Australia typically earn competitive salaries. Entry-level positions offer annual salaries between AUD 60,000 and AUD 80,000, with experienced professionals making over AUD 100,000. This salary range reflects the growing value of data professionals in the workforce.
  • Career Development: The field of data analysis offers significant opportunities for career growth. Analysts can progress from junior roles to senior positions, such as senior data analyst, data scientist, or even data engineer. These growth opportunities make the field an attractive choice for professionals seeking advancement.
  • Flexible Work Environment: Many companies are adopting remote work options, which is particularly appealing for data analysts who value work-life balance. The flexibility to work from home is becoming a key benefit in this field, contributing to its appeal.
  • Cross-Industry Skills: Data analysis skills are transferable across many industries. Analysts can work in sectors such as finance, healthcare, education, and government, providing a diverse range of opportunities. This cross-industry versatility helps ensure job security and long-term career stability.