Course Overview:

Course Title: Data Analytics

Course Duration: 12 Weeks (3 Months)

Course Description: This three-month program is designed for individuals aiming to develop foundational skills in data analytics. Participants will learn the fundamentals of data analysis, statistical techniques, and data visualization using popular tools. Through a combination of theoretical learning, hands-on exercises, and real-world applications, participants will gain proficiency in analyzing and interpreting data.

Detailed Course Outline:

Weeks 1-2: Introduction to Data Analytics

• Understanding Data Analytics

  • Definition and importance of data analytics
  • Role of data analytics in decision-making

• Data Types and Sources

  • Exploring different types of data
  • Sourcing and collecting data for analysis

Weeks 3-4: Data Exploration and Cleaning

• Data Cleaning Techniques

  • Identifying and handling missing data
  • Dealing with outliers and anomalies

• Exploratory Data Analysis (EDA)

  • Visualizing and summarizing data distributions
  • Using descriptive statistics for initial insights

Weeks 5-6: Statistical Analysis

• Introduction to Statistical Concepts

  • Basic statistical terms and concepts
  • Significance testing and hypothesis formulation

• Applying Statistical Tests

  • Performing t-tests, chi-square tests, etc.
  • Interpreting results and drawing conclusions

Weeks 7-8: Data Visualization

• Importance of Data Visualization

  • Communicating insights through visual representations
  • Choosing appropriate visualization tools

• Using Visualization Tools (e.g., Tableau, matplotlib)

  • Creating charts, graphs, and dashboards
  • Design principles for effective data visualization

Weeks 9-10: Introduction to Python for Data Analytics

• Introduction to Python for Data Analysis

  • Setting up Python environments (e.g., Jupyter)
  • Basics of Python programming for data analytics

• Pandas and NumPy Libraries

  • Data manipulation and analysis with Pandas
  • Numerical operations with NumPy

Weeks 11-12: Final Project and Advanced Topics

• Final Data Analytics Project

  • Applying learned concepts to a comprehensive real-world project
  • Analyzing and presenting insights

• Advanced Topics in Data Analytics

  • Machine learning concepts and applications
  • Big data analytics overview (e.g., Hadoop, Spark)

Evaluation and Assessment:

• Weekly assignments, participation in discussions, completion of practical projects, and the final project will be used to assess participants' understanding and application of data analytics skills.