Introduction to Data Analysis
( 25 Modules )

Module #1
Introduction to Data Analysis
Overview of data analysis, importance, and applications

Module #2
Types of Data
Qualitative, quantitative, categorical, and numerical data

Module #3
Data Collection Methods
Surveys, experiments, observational studies, and data sources

Module #4
Data Cleaning and Preprocessing
Handling missing values, outliers, and data transformation

Module #5
Introduction to Data Visualization
Basic plots, charts, and graphs for exploratory data analysis

Module #6
Descriptive Statistics
Measures of central tendency, variability, and data summary

Module #7
Data Distribution and Probability
Understanding normal, binomial, and Poisson distributions

Module #8
Confidence Intervals
Estimating population parameters with confidence intervals

Module #9
Hypothesis Testing
Formulating hypotheses, test statistics, and p-values

Module #10
T-Tests and ANOVA
Comparing means and analyzing variance

Module #11
Correlation and Regression Analysis
Exploring relationships between variables

Module #12
Categorical Data Analysis
Chi-squared tests, contingency tables, and logistic regression

Module #13
Working with Time Series Data
Trends, seasonality, and forecasting

Module #14
Data Mining and Machine Learning
Introduction to supervised and unsupervised learning

Module #15
Data Visualization Tools
Introduction to Tableau, Power BI, or D3.js

Module #16
Python for Data Analysis
Introduction to Pandas, NumPy, and Matplotlib

Module #17
R for Data Analysis
Introduction to R, data manipulation, and visualization

Module #18
Data Analysis with Excel
Using Excel for data analysis, charts, and pivot tables

Module #19
Big Data and NoSQL Databases
Introduction to Hadoop, Spark, and NoSQL databases

Module #20
Data Analysis in Real-World Applications
Case studies from finance, healthcare, marketing, and social sciences

Module #21
Data Storytelling and Communication
Effective reporting and presenting data insights

Module #22
Ethics in Data Analysis
Responsible data handling, bias, and privacy concerns

Module #23
Data Analysis Project Development
Guided project development and feedback

Module #24
Data Analysis Tools and Resources
Overview of popular data analysis tools and resources

Module #25
Course Wrap-Up & Conclusion
Planning next steps in Introduction to Data Analysis career

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Introduction to Data Analysis ( 25 Modules )

Introduction to Data Analysis
( 25 Modules )