Data Science
Beginner to Intermediate
3–6 months
End-to-end data science: statistics, Python, ML models, and how to present insights that drive business decisions.
View course detailsData & AI · Online / Offline
Data Analytics
Learn to clean, analyse, and visualise data to answer business questions using Excel, SQL, and BI tools.
Duration2–4 months
LevelBeginner
ModeOnline / Offline
LocationDombivli East & Online
About this course
Data is at the heart of modern business decisions. Data Analytics helps organizations understand performance, identify trends, solve problems, and make informed decisions. Learn how to organize, clean, analyze, and visualize data using commonly used analytical tools and techniques.
Training is available in Online and Offline modes from our Dombivli East centre at Navare Plaza. Batch timings can be discussed during counselling so the schedule fits students and working professionals.
Key highlights
Data handling
Work with structured datasets and business information.
Data visualization
Present findings through charts, reports, and dashboards.
Analytical thinking
Identify patterns and interpret business trends.
Practical application
Apply analytical methods to realistic business scenarios.
What you gain
- A foundation in data analysis and interpretation.
- Familiarity with essential analytics tools.
- The ability to build meaningful reports and dashboards.
- Project experience to demonstrate your skills, if included in the final course delivery.
Course syllabus
8 modules, taught step by step from fundamentals to practice.
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1
Introduction to Data Analytics
What is data analytics? Types of analytics, data sources, analytics workflow, business questions, and the role of a data analyst.
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2
Microsoft Excel for Data Analysis
Data entry and formatting, formulas and functions, sorting and filtering, conditional formatting, lookup functions, PivotTables, PivotCharts, and summary reports.
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3
Statistics for Data Analytics
Types of data, mean, median, mode, range, variance, standard deviation, distributions, correlation, sampling, and basic hypothesis testing.
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4
SQL and Database Fundamentals
Tables and relationships, SELECT, WHERE, ORDER BY, GROUP BY, aggregate functions, joins, subqueries, CASE statements, and data extraction.
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5
Python for Data Analysis
Python fundamentals, variables, data types, conditions, loops, functions, Jupyter Notebook, NumPy, and Pandas for data manipulation.
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6
Data Cleaning and Preparation
Missing values, duplicates, inconsistent formats, data types, outlier checks, merging datasets, and preparing data for analysis.
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7
Data Visualization and Business Intelligence
Charts and graphs, selecting appropriate visuals, Power BI or Tableau fundamentals, data modeling, relationships, measures, interactive reports, and dashboard design.
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8
Business Analytics and Capstone Project
Define business KPIs, analyze trends, interpret findings, create a final report or dashboard, and present data-driven recommendations.
Learning approach
Concepts
Guided exercises
Dataset practice
Business case studies
Capstone project
Tools & technologies
ME
Microsoft Excel
Spreadsheet analysis, formulas, PivotTables and reporting.
SQL
SQL
Querying, filtering, joining and aggregating data.
Py
Python
Data processing with Pandas and NumPy.
PB
Power BI
Interactive dashboards and business reporting.
Ta
Tableau
Visual analytics and interactive dashboards.
Explore potential career paths
Data Analyst
Analyze datasets and communicate insights.
Business Intelligence Analyst
Build reports and monitor business KPIs.
Reporting Analyst
Prepare reports and track performance metrics.
MIS Analyst / Executive
Manage business data and operational reporting.
Career paths shown are illustrative roles that use these skills; outcomes depend on your effort, background and the job market.
Why choose CIT?
- Career-focused learning: A curriculum aligned with relevant Data Analytics skills.
- Practical approach: Exercises and hands-on practice to reinforce concepts.
- Industry-relevant tools: Learn commonly used tools for Data Analytics.
- Project-based practice: Opportunities to apply concepts to realistic problems, if included in the delivery.
- Learning for different backgrounds: A pathway designed for learners building or expanding their skills.
Who can join?
- College students and graduates
- Freshers exploring data-related careers
- Working professionals looking to upskill
- Beginners interested in Python, analytics, and AI
Common questions
Can I attend Data Analytics Online?
Yes. This course is available in both Online (live sessions) and Offline (Navare Plaza classroom) modes.
Do I need prior experience?
This course is listed as Beginner. Our counsellors will confirm the right starting point based on your background.
How do I get the full syllabus, fees and batch dates?
Fees, syllabus details and batch dates are shared during counselling. Call +91 99672 46501 or send an enquiry.
Start Data Analytics at CIT
Seats and batch timings vary — enquire today for the next available Online or Offline batch.