100% Project Based
Data Analytics

A Data Analytics course teaches how to collect, analyze, and interpret data to make informed decisions. It covers key skills such as data visualization, statistical analysis, and using software tools like Excel, SQL, and Python. The course typically includes topics like data cleaning, exploratory data analysis, predictive analytics, and data-driven decision-making, preparing students to solve real-world problems through data insights. Ideal for those looking to enter fields like business analysis, marketing, finance, and more.

₹30000

About Course
Course Content

A Data Analytics course is designed to teach students the fundamental concepts and techniques used to analyze and interpret data in a meaningful way. The course typically covers a range of topics related to data collection, cleaning, visualization, statistical analysis, and making data-driven decisions.

Key Areas of Focus:

Introduction to Data Analytics:
Understanding the importance and role of data in decision-making.
Overview of the data analytics process and its applications across various industries.
Data Collection & Cleaning:
Methods for gathering data from different sources.
Techniques for cleaning and preparing data for analysis (handling missing values, outliers, and inconsistencies).
Statistical Analysis:
Fundamentals of statistics: mean, median, mode, standard deviation, and probability distributions.
Hypothesis testing, regression analysis, and correlation.
Data Visualization:
How to represent data visually using charts, graphs, and dashboards.
Tools like Tableau, Power BI, or Excel for creating clear and impactful visualizations.
Data Exploration and Descriptive Analytics:
Techniques to summarize and explore data sets.
Descriptive statistics to uncover trends, patterns, and insights.
Predictive Analytics & Machine Learning:
Introduction to predictive models and algorithms (linear regression, decision trees, etc.).
Basics of machine learning and its use in forecasting and decision-making.
Tools and Technologies:
Using tools like Excel, R, Python, SQL, and other analytics software to perform data analysis tasks.
Working with large datasets and understanding data structures.
Ethics and Data Privacy:
Ethical considerations in data collection, analysis, and reporting.
Legal implications and data privacy concerns.

By the end of the course, students will have practical experience in analyzing real-world data, applying statistical methods, and using tools to generate insights that drive business decisions.

This course is ideal for individuals pursuing careers in data science, business intelligence, marketing, finance, or any role requiring data analysis.