Mastering Data Analysis

Beginner
9 sections
35 topics
Duration: 10 weeks

N65000

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What you'll learn


Course content

  • Understanding the Importance of Data Analysis
  • Overview of Data Analysis Workflow
  • Common Data Analysis Challenges and Solutions

  • Introduction to Data Sources
  • Types of data (structured, unstructured)
  • Data formats (CSV, Excel, JSON, etc.)
  • Setting Up Your Data Analysis Environment
  • Installing and Configuring Tools (e.g., Python, Jupyter, R)
  • Introduction to Data Analysis Libraries (e.g., Pandas, NumPy)

  • Descriptive Statistics
  • Measures of Central Tendency and Dispersion
  • Frequency Distributions and Histograms
  • Data Visualization
  • Matplotlib and Seaborn for Python
  • ggplot2 for R

  • Handling Missing Data
  • Outlier Detection and Treatment
  • Data Transformation and Feature Engineering

  • Probability and Probability Distributions
  • Hypothesis Testing
  • Regression Analysis

  • Machine Learning Fundamentals
  • Supervised and Unsupervised Learning
  • Model Evaluation and Validation
  • Clustering and Dimensionality Reduction
  • Time Series Analysis

  • Applying Data Analysis to Business Problems
  • Case Studies and Real-world Examples
  • Industry-specific applications
  • Hands-on projects

  • Introduction to Data Visualization Tools (Tableau, Power BI)
  • Big Data Tools (Hadoop, Spark)
  • Cloud-based Data Analysis Platforms (Google Colab, Azure Notebooks)

  • Developing a Data Analysis Project
  • Presenting and Sharing the Project Results

Requirements

Participants should have a basic understanding of data concepts and access to a computer.

Description

Master the art of data analysis with hands-on courses. Gain advanced skills in statistics, data visualization, and practical applications for informed decision-making.

Who this course is for:

The course is designed for individuals seeking to enhance their data analysis skills, including professionals, students, and anyone interested in leveraging data for informed decision-making.