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Introducing our new Data Analyst Learning Path

It is estimated that over 325 million of terabytes of data is now created daily. Meaning there is a lot of data available to analyse!

Becoming a Data Analyst is therefore a great career option because they are essential for businesses. Data Analysts can use technology to inspect, cleanse, transform, model and visualise data sets identifying trends andinsights for an organisation – enabling them to:

  • Support businesses to improve its strategy and customer experience, and optimise operations
  • Analyse datasets to identify trends, customer insights, business opportunities and/or problems
  • Help organisations to make better business decisions
  • And more…

What will you learn on our Data Analyst Learning Path?

This learning path has been developed in collaboration with IBM and is structured in five steps, and then there are six electives – here’s an outline of each step:

Step 1 – Introduction to Data Analytics Course:
this step will teach you insights into applying data and analytics principles in your business. You’ll also learn about the complete data analytics lifecycle, and use industry-specific examples and case studies to discover how analytics, data visualization, and data science methodologies can be used. By the end of this step, you’ll be able to:

  • Understand how to solve analytical problems in real-world scenarios
  • Define effective objectives for analytics projects
  • Work with different types of data
  • And more…

Step 2 – Business Analytics with Excel:
learners will be able to boost their career with this step, as they will learn new and powerful Microsoft Excel skills. You’ll also be taught data analysis and statistics concepts, for better data-driven decision making. On completion of this step, you’ll have the ability to:

  • Understand the meaning of business analytics and its importance in the industry
  • Grasp the fundamentals of Excel analytics functions and conditional formatting
  • Learn how to analyse with complex datasets using pivot tables and slicers
  • And more…

Step 3 – Programming Basics and Data Analytics with Python:
this step will teach you how to analyse data in Python using multi-dimensional arrays in NumPy, manipulate DataFrames in Pandas, use the SciPy library of mathematical routines, and perform machine learning using scikit-learn. At the end of this step, you’ll be able to:

  • Import data sets
  • Clean and prepare data for analysis
  • Build data pipelines
  • And more…

Step 4 – Tableau Training:
this step will enable learners to build visualisations, organise data, and design charts and dashboards. You’ll also learn about Data Visualisation concepts, different combo charts, and stories, working with filters, parameters, and sets, and building interactive dashboards. After you’ve finished this step, you’ll be able to:

  • Become an expert on visualization techniques such as heat map, treemap, waterfall, Pareto
  • Understand metadata and its usage
  • Learn how to build charts, interactive dashboards, story interfaces, and how to share your work
  • And more…

Step 5 – Data Analyst Capstone:
the final step of this learning path will help you apply your learned skills to solve a real industry-aligned Data Science problem. This Capstone course will also be based on the Data Science decision cycle, and these are the four project milestones:

After all steps have been completed in line with the required criteria, learners will receive a ‘Certificate of Achievement’ from Simplilearn and a ‘Data Analytics with Python’ certificate from IBM. As part of the learning path, learners will also have access to these electives:

  • Power BI
  • Programming Refresher
  • R Programming for Data Science
  • Data Science with R Programming
  • SQL Training
  • Industry Master Class – Data Analytics

How is the learning path delivered?

This Data Analytics Learning Path is delivered digitally using:

  • Online self-learning: consisting of videos and quizzes
  • Live interactive classes: via virtual classrooms with live interaction and monitoring
  • Hands-on experience: through final assessment, project work and virtual labs

Want to learn more?

Visit ILX.com where you can download our brochure and book training.