SafeNet

Descriptive Statistics: Mean, median, mode, variance, standard deviation
Probability: Basic probability concepts, distributions (normal, binomial)
Inferential Statistics: Confidence intervals, hypothesis testing
Linear Algebra: Vectors, matrices (basics for data manipulation)

Data Analytics Roadmap

Follow this roadmap to develop expertise in Data Analytics

Learn the basics of statistics, probability, and mathematics required for data analysis, along with essential tools like Excel and SQL.

Master techniques for gathering data from various sources including web scraping, APIs, and database queries with SQL.

Learn techniques for cleaning, transforming, and preparing data for analysis, including handling missing values and outliers.

Develop skills to create effective visualizations and dashboards using tools like Tableau, Power BI, and Python libraries.

Take your skills further with statistical analysis, A/B testing, and introductory machine learning for predictive analytics.