Course Overview
Curriculum
What is Data Analytics?
Importance of Data Analytics in Business
Types of Data Analytics: Descriptive, Diagnostic, Predictive, Prescriptive
Basic Functions and Formulas
Arithmetic Operations
Statistical Functions
Data Cleaning and Preparation
Removing Duplicates
Data Formatting
Data Visualization
Charts and Graphs
Conditional Formatting
Pivot Tables and Pivot Charts
Creating and Analyzing Pivot Tables
Understanding Databases
Basic SQL Commands : SELECT, INSERT, UPDATE, DELETE
Filtering Data
Joins and Subqueries
Joins and Subqueries
INNER JOIN, LEFT JOIN, RIGHT JOIN
Writing Subqueries
Python Basics
Syntax and Data Types
Control Structures (Loops and Conditionals)
Working with Libraries
Installing Libraries (pip)
Introduction to Jupyter Notebook
DataFrames and Series
Data Cleaning and Preparation
Handling Missing Data
Filtering and Selecting Data
Data Aggregation and Grouping
Merging and Joining Data Frames
Introduction to NumPy
Arrays and Their Properties
Array Operations
Mathematical Functions
Statistical Functions
Data Visualization with Power BI
Introduction to Power BI
Power BI Desktop vs. Power BI Service
Data Importing and Preparation
Connecting to Data Sources
Data Transformation using Power Query
Creating Reports and Dashboards
Visualizations: Charts, Tables, Maps
Slicers and Filters
Introduction to Tableau
Connecting to Data Sources
Creating Basic Visualizations
Bar Charts, Line Charts, Scatter Plots
Building Dashboards
Combining Visualizations
Interactivity in Dashboards
Real-world Data Analysis Project
Applying Skills Learned
Data Collection, Cleaning, Analysis, and Visualization
Presentation of Findings
Introduction to Git and GitHub
Setting Up a GitHub Account
Basic Git Commands
Git init, Git add, Git commit, Git push
Collaborating on GitHub
Forking and Cloning Repositories
Pull Requests
Task management
Communication Skills
Presentation Skills
- Resume Prep
- LinkedIn
- Job Hunting & outreaching
- Interview Preparation
- Mock Interviews
FAQs
It is a self-paced course that provides the students with the key skills necessary for a career in data analytics.
Yes, placement support is included for eligible students.
Yes, a recognized certificate is awarded upon successful completion.
Yes, STAD Solution offers flexible, self-paced learning options.
Yes, recorded sessions are available for future reference.
Yes, projects and case studies are included for practical learning.
Training is delivered online, with interactive sessions and resources.
Yes, STAD Solution offers career coaching, resume help, and interview prep.
Tools include Python, SQL, Power BI, and Tableau.
Yes, working professionals can also join the flexible online course.
The duration is usually 3 to 6 months.
Of course, it is meant for absolutely no experience, there are all the basic concepts being taught.
Basic math and analytical skills would be an advantage but are not mandatory.
It has a course structure as per industry requirements, great mentors and hands-on opportunities.
Topics like data cleaning, data manipulation, data visualization, etc. and also important tools.