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ELITEMIND  CONSULTANCY AND TRAINING  –  L.L.CELITEMIND  CONSULTANCY AND TRAINING  -  L.L.C
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Data Analysis

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  • Data Analysis

Data Analysis

  • By waseem khan
  • Data Analysis
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    • Transform raw data into insights using analytical tools and techniques.

      Course Content

      Course Objective

      • Understand the data analysis lifecycle
      • Use tools like Excel, Power BI, Python, and SQL
      • Learn how to interpret data, visualize trends, and support data-driven decision-making

      Module 1: Introduction to Data Analysis

      • What is Data Analysis?
      • Types of Data: Qualitative vs Quantitative
      • Structured vs Unstructured Data
      • Data lifecycle and its stages

      Module 2: Data Collection & Cleaning

      • Data sources (files, databases, APIs, web scraping)
      • Data cleaning techniques
      • Handling missing data and outliers
      • Data types and conversions

      Module 3: Excel for Data Analysis

      • Functions: VLOOKUP, IF, INDEX/MATCH, etc.
      • Pivot Tables & Charts
      • Data validation and conditional formatting
      • What-If Analysis and Goal Seek

      Module 4: SQL for Data Handling

      • Basics of relational databases
      • SELECT, WHERE, JOIN, GROUP BY
      • Data aggregation and filtering
      • Subqueries and views

      Module 5: Python for Data Analysis (Intro Level)

      • Using libraries: Pandas, NumPy
      • DataFrames and Series operations
      • Importing and exporting data (CSV, Excel, JSON)
      • Data transformation and summary stats

      Module 6: Data Visualization

      • Principles of effective visualization
      • Excel charts, Power BI, and Python (Matplotlib/Seaborn)
      • Dashboards using Power BI/Tableau (optional)
      • Storytelling with data

      Module 7: Statistical Concepts

      • Descriptive statistics: mean, median, mode, std deviation
      • Inferential statistics: correlation, regression
      • Hypothesis testing basics
      • Data distributions and probability

      Module 8: Exploratory Data Analysis (EDA)

      • Identifying patterns and relationships
      • Detecting anomalies and trends
      • Summary reports and insights generation
      • EDA using Python or Power BI

      Module 9: Final Project

      • Choose a real-world dataset
      • Perform end-to-end analysis
      • Present findings via a dashboard or report

      A course by

      WK
      waseem khan

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      Course Includes:

      • Price:Free
      • Instructor:waseem khan
      • Lessons:38
      • Students:0
      • Level:All Levels
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