Who this course is for
- Graduates who want an entry point into data roles
- Commerce, science, engineering, and business students who enjoy analysis
- Working professionals who want reporting, dashboarding, and Python analytics skills
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Data Science
Applied Data Science & ML
A Data Analytics course teaches how to collect, clean, analyse, visualize, and interpret data for business decision-making. Includes Excel, SQL, Python, statistics, Power BI/Tableau, and real-world projects.
6 months
Hybrid live
10 modules · 54 topics
What you'll achieve
Statistics, ML models, dashboards, data storytelling, and analytics case interviews.
Job roles to target
Data AnalystBusiness AnalystJunior Data ScientistMIS AnalystAnalytics Associate
Tools and skills covered
ExcelSQLPythonPandasPower BITableauStatisticsMachine Learning basics
Full Syllabus
1
Module 1: Introduction to Data Analytics
- What is Data Analytics
- Types of Analytics — Descriptive, Diagnostic, Predictive, Prescriptive
- Data Analytics Lifecycle
2
Module 2: Advanced Excel for Analytics
- Excel Interface & Shortcuts
- Formulas & Functions
- Logical Functions
- Lookup Functions (VLOOKUP/XLOOKUP)
- Pivot Tables
- Charts & Dashboards
- Conditional Formatting
- Data Cleaning in Excel
- What-if Analysis
3
Module 3: Statistics for Data Analytics
- Mean, Median, Mode
- Standard Deviation & Variance
- Probability Basics
- Correlation & Regression Basics
- Sampling Techniques
- Hypothesis Testing
4
Module 4: SQL for Data Analytics
- Database Fundamentals
- SQL Queries & SELECT Statements
- Filtering Data
- Aggregate Functions
- GROUP BY & HAVING
- Joins & Subqueries
- Views & Stored Procedures
- Window Functions
5
Module 5: Python for Data Analytics
- Python Fundamentals — Variables, Data Types, Loops, Functions, File Handling
- Libraries — NumPy, Pandas, Matplotlib, Seaborn, OpenPyXL
- Data Handling — Cleaning, Missing Values, Transformation, Aggregation
6
Module 6: Data Visualization
- Power BI — Desktop, Data Import, Data Modeling, DAX Basics, Dashboard Creation, Reports & Publishing
- OR Tableau — Interface, Charts & Dashboards, Storytelling with Data, Filters & Parameters
7
Module 7: Data Cleaning & Preparation
- Data Wrangling
- Handling Null Values
- Removing Duplicates
- Data Formatting
- Outlier Detection
- Feature Engineering Basics
8
Module 8: Exploratory Data Analysis (EDA)
- Understanding Data Patterns
- Trend Analysis
- Correlation Analysis
- Business Insights Generation
- Visualization Techniques
9
Module 9: Business Analytics Concepts
- KPI Metrics
- Business Reporting
- Customer Analytics
- Sales Analytics
- Financial Analytics
- Marketing Analytics
10
Module 10: Tools & Learning Path
- SQL (MySQL/PostgreSQL)
- Python
- Power BI
- Tableau
- Jupyter Notebook
- Google Sheets
What You'll Build
These are the projects you'll complete during the course — each one is deployable, portfolio-ready, and designed to demonstrate real skills to hiring teams.
Note: Projects and tools may be updated between batches based on industry trends, trainer expertise, and current hiring patterns. The goal remains the same — you leave with work you can show employers.
Sales Performance Dashboard
Interactive Power BI dashboard tracking regional sales, rep performance, product mix, and quarterly trends from raw Excel data.
ExcelPower BIDAXSQL
Customer Churn Analysis
Identify which customers are likely to leave using Python. Clean the dataset, find patterns, and present actionable findings.
PythonPandasMatplotlibSeabornJupyter
E-Commerce Funnel Report
SQL-driven analysis of where shoppers drop off from browse to purchase. Visualized as a Tableau story with recommendations.
SQLTableauGoogle Sheets
HR Attrition Insights
Explore employee exit data to find department-level patterns. Build a Power BI report with filters for management review.
ExcelPower BIPythonPandas
Applied Data Science & ML training in Bengaluru
This course is built for Bengaluru fresher hiring patterns: fundamentals, hands-on projects, interview explanation, and portfolio proof. Learners can attend from Bengaluru and discuss batches, fees, and placement-readiness with the admissions team.
Format
Hybrid live
Duration
6 months
Support
Projects + interview prep
Bengaluru fresher salary and hiring context
Typical fresher analytics roles in Bengaluru often start around Rs. 3.5L to Rs. 6L per annum, with better outcomes for SQL, dashboarding, and case-study portfolios.
Salary ranges are directional and depend on background, project quality, communication, interview performance, and employer requirements.
What recruiters usually check
- SQL queries
- Excel and dashboard clarity
- Python/Pandas basics
- Business interpretation
- Ability to explain insights, not just charts
Related career guides
Career Guide
Python vs Java for Freshers — An Honest Take From Someone Who Teaches Both
Stop asking the internet which language is "better." Here's how to decide based on what kind of job you want in Bangalore.
Interview Prep
What Bangalore Hiring Managers Actually Look For (I Asked 12 of Them)
Straight from the people who decide whether you get the job — what matters, what doesn't, and what annoys them about fresher candidates.
Frequently asked questions
Is data analytics a good IT career path for freshers?
Yes. Data analytics is a practical entry path for freshers who can learn Excel, SQL, Python, dashboards, and business problem-solving with real datasets.
Do I need advanced maths for this course?
No. You need comfort with basic statistics and logical thinking. The course builds the required analytics concepts step by step with business examples.
What kind of portfolio will I build?
Learners create dashboards, SQL analysis, Python notebooks, EDA reports, and business case studies that can be shown during interviews.
Ready to start Applied Data Science & ML?
Get batch details, fees, and a personalized learning plan from our admissions team.
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