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Who should take this class?

  • Aspiring Data Analysts who desire to start a career in data analytics and learn the skills required to become skilled data analysts
  • Managers, consultants, and other business professionals who want to use data analytics to make better decisions and expand their businesses.
  • Students and recent graduates who wish to master data analytics to advance their careers.
  • System administrators, database administrators, and other IT professionals who desire to broaden their knowledge of data analytics.
  • Marketing and sales professionals who want to evaluate consumer data, track trends, and optimize campaigns with data-driven insights.
  • Finance professionals interested in utilizing data analytics for financial forecasts, risk assessment, and performance evaluation.
  • Professionals in healthcare who seek to apply data analytics to improve patient care, track health trends, and improve overall healthcare results.
  • Researchers and academics from a variety of disciplines who want to master data analytics approaches for assessing research data and reaching evidence-based conclusions
  • Freelancers and entrepreneurs interested in developing or maintaining data-driven projects or providing data analytics services to clients.

Data Analytics with IDEaL

Data Analytics teaches students how to successfully analyze, interpret, and convey data insights. Data gathering, data preprocessing, statistical analysis, and data visualization techniques are all covered in this course. Students acquire hands-on experience with software and programming languages such as Excel, SQL, Python, and Tableau. Graduates are equipped to work as data analysts, business analysts, or data visualization specialists, assisting firms in making data-driven decisions

Learning Objectives

  • Understand important ideas in data analytics such as data cleansing, data exploration, data visualization, and statistical analysis.
  • Learn how to use major data analytics tools and programming languages including Python, Excel, and Tableau.
  • Learn how to obtain, clean, and preprocess raw data before analyzing it to ensure accurate and trustworthy findings.
  • Learn how to use various data visualization approaches to successfully communicate ideas and discoveries to both technical and non-technical audiences.
  • To draw meaningful inferences from data, master basic statistical analysis techniques such as hypothesis testing, regression analysis, and time series forecasting.
  • Learn how to use machine learning algorithms to find hidden patterns, anticipate outcomes, and drive data-driven decision-making.
  • Learn how to work with many sorts of data, including structured, unstructured, and streaming data.
  • Learn how to utilize data analytics to address real-world business challenges and make informed decisions in a variety of industries, including banking, marketing, and healthcare.
  • Improve your critical thinking and problem-solving abilities in order to tackle complicated data difficulties and provide meaningful insights.
  • Gain experience working on real-world data analytics projects while developing a solid portfolio to offer future employers your talents and expertise.