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PAS

Data Analytics by ITS

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By CapaGenius Categories: PAS
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About Course

Kick Start on a transformative journey into the world of data analytics with our comprehensive Data Analytics program designed for Information Technology Specialists. Throughout this immersive 8-week course, students will dive deep into the fundamentals of data analysis, manipulation, and visualization, while also exploring cutting-edge techniques and tools used in the field of artificial intelligence.

In the first week, students will lay the foundation by understanding the concept of data and its various types, followed by learning essential data manipulation techniques in the subsequent weeks. From importing and cleaning data to advanced manipulation methods and data analysis fundamentals, students will gain practical skills to effectively extract insights from complex datasets.

As the course progresses, students will explore the role of artificial intelligence in data analysis, uncovering the potential applications and benefits of machine learning algorithms. They will also delve into the art of data visualization, mastering techniques to present data effectively and derive meaningful insights.

Moreover, the program emphasizes responsible analytics practices, equipping students with the knowledge of data privacy laws, ethical considerations, and bias mitigation strategies. By the end of the course, students will have the opportunity to apply their newfound skills in a capstone project, where they will showcase their proficiency in data analytics principles and techniques.

By enrolling in our Data Analytics program, students will not only gain in-depth knowledge and hands-on experience but also open doors to exciting career opportunities in the rapidly evolving field of data analytics. Whether aspiring to become data analysts, data scientists, or IT specialists, this program serves as a stepping stone towards a successful and rewarding career in information technology.

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Course Content

Week 1 – Introduction to Data Basics

  • Understand the concept of data and its importance in analytics
  • Learn about basic data variable types such as Boolean, numeric, and string
  • Explore basic structures used in data analytics, including tables, rows, columns, and lists
  • Discuss different data categories, including qualitative, quantitative, structured, unstructured, metadata, and big data

Week 2 – Data Manipulation Techniques

  • Learn how to import, store, and export data
  • Understand the ETL (Extract, Transform, Load) process and common data manipulation tools such as SQL, R, Python, and Microsoft Excel
  • Explore common data storage file formats such as delimited data files, XML, and JSON
  • Practice cleaning data by handling NULL values, special characters, and inconsistent formatting

Week 3 – Advanced Data Manipulation

  • Dive deeper into data cleaning techniques and practices
  • Learn how to organize data using sorting, filtering, slicing, transposing, and other techniques
  • Explore data aggregation methods including grouping, joining/merging, summarizing, and pivoting

Week 4 – Data Analysis Fundamentals

  • Describe and differentiate between types of data analysis, including descriptive, diagnostic, hypothesis testing, predictive, and prescriptive analysis
  • Understand data aggregation and interpretation metrics such as aggregate functions and exploratory data analysis methods
  • Evaluate and explain the results of data analyses, including trends, expected values, and interpret results of predictive models

Week 5 – Introduction to Artificial Intelligence in Data Analysis

  • Define artificial intelligence, machine learning, and algorithms
  • Describe how AI is used in data analysis and the role of machine learning algorithms
  • Explore the potential applications of AI in data analytics

Week 6 – Data Visualization Techniques

  • Learn how to effectively report and present data using tables and charts
  • Explore best practices for creating visualizations from data, including different visualization types and when to use them
  • Derive conclusions from data visualizations and understand the importance of accurate representation

Week 7 – Responsible Analytics Practices

  • Understand data privacy laws and best practices, including GDPR, FERPA, HIPAA, IRB, and PCI
  • Learn best practices for responsible data handling, including methods of handling PII and securing data
  • Discuss different types of bias that affect data collection and interpretation and how to mitigate them

Week 8 – Capstone Project

  • Apply the knowledge and skills learned throughout the course to complete a data analytics project
  • Present findings and insights from the project to demonstrate understanding and proficiency in data analytics principles and techniques
₹9,999.00 ₹14,999.00
  • All Levels
  • August 12, 2024 Last Updated
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