Requirements
- Basic 12th pass or equivalent education (any stream)
- Comfortable with using a computer and the internet
- Basic math skills (like percentages, averages, and simple statistics)
- Willingness to learn tools like Excel, SQL, Power BI, and Python
- Curiosity for data and problem-solving mindset
- No prior programming experience needed (if beginners course)
- Laptop or desktop with good internet connection for online learning
Features
- Live Project-Based Training
- Expert-Led Sessions
- Flexible Learning Options
- Interactive Learning
- Smart Labs with Advanced Equipment
- Unlimited Lab Access
- Comprehensive Study Material
- Globally Recognized Certification
- One-on-One Mentorship
- Career Readiness
- Job Assistance
Target audiences
- Students after 12th and college learners looking for job-oriented skills
- Fresh graduates from any stream (Commerce, Science, Arts, IT, Management)
- Working professionals seeking career growth and salary improvement
- IT professionals planning to move into analytics and business roles
- Non-technical background learners entering the tech industry
- Career switchers looking for high-demand job opportunities
- MBA students and management professionals enhancing decision-making skills
- Entrepreneurs and business owners using data for business growth
- Job seekers preparing for placements and interviews
- Freelancers and remote job aspirants building analytics portfolios
Data Analytics Course in Noida with Placement | Data Analytics Training in Noida
If you’re searching for a data analytics course in Noida with placement, your main goal is simple: learn real skills and get a job. At Ascents Learning, we don’t just teach tools—we help you build a career.
Our program is made for Indian students (12th pass, undergraduates, graduates, and freshers) who want a clear, job-focused roadmap. You’ll learn through 100% practical training, work on live industry projects, build a strong portfolio, and get support from our dedicated placement cell.
Here’s what makes us different:
“From Learning to Earning – We Prepare You for the Real IT Industry.” “Not Just Training, We Build Careers.”
So if you’re looking for the best institute for data analytics in Noida, a trusted data analytics course institute in Noida, or even a data analytics training center near me, this page will show you exactly what you get at Ascents Learning.
Why Data Analytics Is a Smart Career Choice in 2026
Every company today runs on data—sales numbers, customer behavior, marketing performance, product demand, and business growth. That’s why data analytics has become one of the most in-demand career paths for students and freshers.
A data analyst helps companies by:
- Cleaning and organizing data
- Creating dashboards and reports
- Finding patterns and insights
- Helping teams take better decisions
This is why students are actively choosing a data analyst course in Noida, especially a data analyst course in Noida with placement.
What is Data Analytics
Data analytics means understanding data to solve real business problems.
Example:
- A company wants to know: “Which product is selling more and why?”
- A food delivery app wants to know: “Which areas order most on weekends?”
- A coaching institute wants to know: “Which ads bring the best students?”
In a data analytics course in Noida, you learn how to answer these questions using tools like Excel, SQL, and Power BI (and optional Python). You also learn how to present your findings in a way that companies understand.
Ascents Learning: Data Analytics Training in Noida That Leads to Jobs
Many institutes offer a data analytics course in Noida, but students mostly care about one thing—career outcome.
At Ascents Learning, our training is built around:
- Practical learning
- Projects and portfolio
- Interview preparation
- Placement support (real support, not just “assistance”)
If you want data analytics training Noida that prepares you for real hiring, you’re in the right place.
Career & Placement Focus
– 100% Placement Support (not just “assistance”)
– Dedicated Placement Cell
– 200+ Hiring & Industry Partner Companies
– Guaranteed Interview Calls (after course completion)
– Mock interviews with industry experts
– Resume, LinkedIn & portfolio building support
– Soft skills & HR interview preparation
– Career counseling & job role mapping
“Not Just Training, We Build Careers.”
Training Quality & Practical Exposure
– 100% Practical, Hands-On Training
– Live industry projects (real client scenarios)
– Case studies from real companies
– Weekly assignments & assessments
– Capstone project at course end
– Project review by industry mentors
– Tools & technologies used in real companies
“100% Practical Training with Real-World Projects.”
Faculty & Mentorship
– 10+ years industry expert trainers
– Working professionals as mentors
– 1:1 doubt-clearing sessions
– Small batch size for personal attention
– Trainer support even after course completion
Certification & Internship
– Industry-recognized certification
– Internship letter / experience letter
– Live internship with ongoing projects
– Project completion certificate
– Certification aligned with industry standards
This makes Ascents Learning a strong option if you want a Data analytics course with certification that actually adds value to your resume.
Learning Flexibility
– Online + Offline / Hybrid classes
– Weekday & weekend batches
– Recorded session access
– Lifetime learning access (updated content)
– Fast-track & regular batch options
Additional Value (Big Differentiators)
– AI tools & automation training (latest trend)
– Personal mentorship for career growth
– Freelancing & startup guidance
– Entrepreneurship support
– Hackathons, workshops & tech events
– Community access (alumni + peer network)
Student-Friendly Benefits
– Affordable fee structure
– Easy EMI / installment options
– Scholarships for deserving students
– Free demo classes
– No-cost career guidance session
Course Overview: Data Analyst Course in Noida (Job-Ready Curriculum)
This is not a theory-based program. This is a job-focused course designed for students who want to start working as a data analyst.
Our course covers:
1) Advanced Excel for Data Analytics
– Data cleaning and formatting
– Important formulas (IF, SUMIFS, COUNTIFS, XLOOKUP)
– Pivot tables and reports
– Dashboard basics
2) SQL for Data Analysts
– Writing queries using SELECT, WHERE, ORDER BY
– JOINs (must for interviews)
– GROUP BY and aggregation
– Subqueries and case-based practice
3) Power BI for Business Dashboards
– Data modelling basics
– DAX introduction
– Visual dashboards with filters
– Real business dashboards
4) Statistics & Business Metrics (Easy Level)
– Mean, median, standard deviation
– Trend understanding
– Business KPIs and reporting
5) Live Projects + Capstone
– Weekly mini projects
– Final capstone project
– Mentor review and improvements
This structure is why students consider Ascents Learning as the best data analytics training institute in Noida for practical learning.
Live Industry Projects (Real Work Experience)
Students get hands-on practice with projects such as:
- Sales dashboard (region, category, monthly growth)
- Customer analysis (repeat customers, retention)
- Marketing campaign performance (ROI, leads, conversion)
- HR analytics (attrition and hiring trends)
- Operations reporting (delivery time, service performance)
These projects help you build a portfolio which is essential for a data analytics course in Noida with placement.
How to Become a Data Analyst (Clear Roadmap)
If your goal is a job, follow this step-by-step plan:
Step 1: Start with Excel
Excel is still used in companies daily. You’ll learn advanced reporting skills.
Step 2: Learn SQL
SQL helps you extract data from databases—one of the most important job skills.
Step 3: Build Dashboards using Power BI
Dashboards make you stand out and show your work clearly.
Step 4: Create 3–5 Strong Projects
Projects are the proof that you can work like a real analyst.
Step 5: Prepare for Interviews + Get Placement Support
Mock interviews, HR training, resume building, and interview calls after completion.
This is exactly what we offer in our data analyst course in Noida with placement.
Skills Required to Become a Data Analyst
You don’t need to be a coding expert. You need:
Logical thinking and problem-solving
Communication skills (explaining insights)
Basics of math and statistics
Tool knowledge (Excel, SQL, Power BI)
Consistent practice
Our mentorship and weekly assessments make sure you improve step-by-step.
Demand, Future & Vacancies for Data Analysts
Demand of Data Analysts
Data roles are growing because businesses now track every activity using data.
Future of Data Analyst
Analytics is a long-term career skill and also a base for data science and AI roles.
Vacancies for Data Analyst
Common entry-level roles students apply for:
– Data Analyst (Fresher)
– MIS Executive / MIS Analyst
– Reporting Analyst
– Business Analyst (junior)
– Power BI Developer (junior)
Our job role mapping and career counseling help you choose the right path.
Data Analytics Course Fees in Noida (Student-Friendly Options)
Students often compare data analytics course fees in Noida before joining. Fees depend on:
- Duration (fast-track or regular)
- Modules included (Excel/SQL/Power BI + add-ons)
- Projects and mentorship
- Placement preparation support
- Internship and certification benefits
At Ascents Learning, we offer:
- Affordable fee structure
- Easy EMI / installment options
- Scholarships for deserving students
- Free demo classes
If you’re searching for a Data analyst course in Noida with fees, contact us to get the latest batch-wise fee plan.
Why Students Call Us the Best Institute for Data Analytics in Noida
Students choose us because we focus on real outcomes:
- Practical learning (not boring theory)
- Live projects and capstone
- Dedicated placement cell
- Guaranteed interview calls (after completion)
- Small batches and 1:1 support
- Resume + LinkedIn + portfolio help
- AI tools and automation training
“Train with Industry Experts, Get Placed with Top Companies.” “Learn Skills That Companies Actually Hire For.”
Start Your Data Analytics Career with Ascents Learning
If your goal is to learn real skills and get job-ready, choose Ascents Learning for the most practical **data analytics course in Noida**.
“From Learning to Earning – We Prepare You for the Real IT Industry.”
Curriculum
- 61 Sections
- 359 Lessons
- 20 Weeks
- Module 1: Excel Basics for BeginnersTools Covered: Microsoft Excel (All Versions)8
- 1.1Understanding Excel Interface and Ribbon
- 1.2Working with Workbooks, Worksheets, and Cells
- 1.3Entering and Formatting Data
- 1.4Basic Excel Formulas and Functions (SUM, AVERAGE, MIN, MAX)
- 1.5Using AutoFill and Flash Fill
- 1.6Basic Formatting (Fonts, Colors, Borders, Cell Styles)
- 1.7Adjusting Rows, Columns, and Cell Sizes
- 1.8Basic Excel Shortcuts for Efficiency
- Module 2: Data Entry, Cleaning, and FormattingTools Covered: Excel Formatting, Data Cleaning Tools6
- Module 3: Working with Formulas and FunctionsTools Covered: Excel Formulas, Logical and Lookup Functions5
- 3.1Understanding Relative, Absolute, and Mixed References
- 3.2Logical Functions (IF, AND, OR, IFERROR, IFS)
- 3.3Lookup and Reference Functions (VLOOKUP, HLOOKUP, XLOOKUP, INDEX-MATCH)
- 3.4Date and Time Functions (TODAY, NOW, DATEDIF, NETWORKDAYS)
- 3.5Text Manipulation with String Functions (TEXT, UPPER, LOWER, PROPER)
- Module 4: Data Visualization with Charts and GraphsTools Covered: Excel Charts and Graphs5
- Module 5: Data Analysis with Pivot Tables and Pivot ChartsTools Covered: Excel Pivot Tables and Pivot Charts6
- Module 6: Advanced Excel Functions for Data AnalysisTools Covered: Excel Advanced Formulas and Functions5
- Module 7: Power Query and Power Pivot for Data ModelingTools Covered: Power Query, Power Pivot5
- Module 8: Working with Large Datasets and Advanced Excel ToolsTools Covered: Excel Data Management5
- Module 9: Excel for Business Intelligence and ReportingTools Covered: Power BI, Excel Dashboards4
- Module 10: Projects and Interview PreparationTools Covered: Excel, Power Query, Power Pivot4
- Module 11: Introduction to Databases and SQLTools Covered: MySQL, Microsoft SQL Server, PostgreSQL5
- Module 12: SQL Basics – Writing QueriesTools Covered: SQL Query Editor, MySQL Workbench, SSMS6
- Module 13: Advanced Data Retrieval and FilteringTools Covered: SQL Querying Tools5
- Module 14: Aggregations and Grouping DataTools Covered: SQL Functions and Queries4
- Module 15: Working with Joins and RelationshipsTools Covered: SQL Joins and Relationships5
- Module 16: Advanced SQL for Data AnalysisTools Covered: SQL Advanced Queries5
- Module 17: SQL Performance Optimization and IndexingTools Covered: SQL Server / MySQL Performance Tools5
- Module 18: SQL for Data Analysis and ReportingTools Covered: SQL Reporting and Visualization4
- Module 19: Real-World Projects and Interview PreparationTools Covered: SQL, Power BI, Excel4
- Module 20: Introduction to Python16
- 20.1Overview of Python
- 20.2History and Versions of Python
- 20.3Features of Python:
- 20.4Simple and Open Source
- 20.5High-Level Programming Language
- 20.6Portable and Interpreted
- 20.7Object-Oriented & Procedural
- 20.8Easy to Maintain
- 20.9Comparison of Python with Other Languages
- 20.10Java vs. Python
- 20.11C++ vs. Python
- 20.12JavaScript vs. Python
- 20.13Perl vs. Python
- 20.14Executing Python Programs
- 20.15Python Interactive Mode vs. Script Mode
- 20.16Comments in Python
- Module 21: Python Variables & Data Types11
- Module 22: Operators in Python10
- Module 23: Conditional Statements in Python3
- Module 24: Looping in Python7
- Module 25 Working with Numbers in Python3
- Module 26: Working with Strings in Python4
- Module 27: Working with Lists in Python7
- Module 28: Working with Tuples in Python4
- Module 29: Working with Dictionaries in Python4
- Module 30: Working with Sets in Python4
- Module 31: Date & Time Handling in Python2
- Module 32: Functions in Python5
- Module 33: Working with Modules in Python4
- Module 34: File Handling in Python (I/O Operations)4
- Module 35: Exception Handling in Python6
- Module 36: Object-Oriented Programming (OOP) in Python5
- Module 37: Introduction to Anaconda DistributionPython Modules Curriculum Pandas, Numpy, Matplotlib and Seaborn7
- 37.1🛠 Tools Covered: Anaconda, Python, Jupyter Notebook, PyCharm
- 37.2What is Anaconda Distribution?
- 37.3Difference between Anaconda and Python Distribution
- 37.4How to install Anaconda?
- 37.5Anaconda Repository: Understanding conda packages and environments
- 37.6Anaconda Navigator: Managing libraries and environments
- 37.7Integrating Anaconda with PyCharm for seamless coding
- Module 38: Using Git and GitHub🛠 Tools Covered: Git, GitHub5
- Module 39: Introduction to NumPy & Statistical AnalysisTools Covered: NumPy, Python7
- Module 40: Introduction to Pandas & Data AnalysisTools Covered: Pandas, Python8
- 40.1What is Pandas?
- 40.2Creating Pandas Series and DataFrames
- 40.3Grouping, Sorting, and Filtering Data
- 40.4Merging, Joining, and Concatenating DataFrames
- 40.5Handling Missing Data (Imputation Techniques)
- 40.6Pandas Operations for Data Analysis
- 40.7Data Input and Output (CSV, Excel, JSON, Databases)
- 40.8Hands-on Practical Use Cases using Pandas
- Module 41: Statistics and ProbabilityConcepts Covered: Statistical Analysis, Probability Theory9
- 41.1Types of Datasets: Numerical, Categorical, Ordinal
- 41.2Descriptive Statistics: Mean, Median, Mode
- 41.3Variance & Standard Deviation
- 41.4Probability Functions:
- 41.5Probability Density Function (PDF)
- 41.6Probability Mass Function (PMF)
- 41.7Percentiles and Moments
- 41.8Covariance vs Correlation
- 41.9Conditional Probability & Bayes’ Theorem
- Module 42: Data Visualization using MatplotlibTools Covered: Matplotlib, Python7
- 42.1Understanding Exploratory Data Analysis (EDA)
- 42.2Plotting Line Graphs on Time-Series Data
- 42.3Pie Charts, Bar Charts, and Horizontal Bar Graphs
- 42.4Introduction to the IRIS Dataset
- 42.52D Scatter Plots & Pair Plots
- 42.6Histograms & Probability Density Function (PDF)
- 42.7Cumulative Distribution Function (CDF)
- Module 43: Data Visualization using SeabornTools Covered: Seaborn, Python5
- Module 44: Project & Interview PreparationProjects, Career Guidance & Resume Building7
- 44.1Hands-on Real-World Projects
- 44.2E-commerce Data Analysis
- 44.3Retail Sales Forecasting
- 44.4Customer Segmentation using SQL & Pandas
- 44.5Soft Skills & PD (Personality Development) Classes
- 44.6Resume Preparation & Optimization for Data Analyst Roles
- 44.7Common Interview Questions & Mock Interview Sessions
- Module 45: Quick Start with Power BI ServicePower BI Course Curriculum (Beginner to Advanced) | Tools Covered: Power BI Service, Power BI Desktop6
- Module 46: Getting and Transforming Data with Power BI DesktopTools Covered: Power BI Desktop, Power Query Editor6
- Module 47: Data Modeling in Power BITools Covered: Power BI Desktop7
- Module 48: Data Visualization in Power BITools Covered: Power BI Desktop20
- 48.1Creating Different Types of Visualizations
- 48.2Formatting and Customizing Visualizations
- 48.3Setting Sort Order for Visuals
- 48.4Using Scatter and Bubble Charts with Play Axis
- 48.5Tooltips and Interactive Reports
- 48.6Slicers, Timeline Slicers, and Sync Slicers
- 48.7Cross Filtering and Highlighting
- 48.8Applying Visual, Page, and Report Level Filters
- 48.9Drill Down and Drill Up Functionality
- 48.10Working with Hierarchies
- 48.11Adding Reference and Constant Lines
- 48.12Creating Tables and Matrices with Conditional Formatting
- 48.13Using KPI Indicators, Cards, and Gauges
- 48.14Map Visualizations
- 48.15Importing and Using Custom Visuals
- 48.16Managing and Arranging Visuals in Reports
- 48.17Implementing Drill-through for In-depth Analysis
- 48.18Using Custom Report Themes
- 48.19Grouping and Binning Data
- 48.20Working with Selection Pane, Bookmarks, and Buttons
- Module 49: Power BI Service Visualization ToolsTools Covered: Power BI Service5
- Module 50: Publishing and Sharing ReportsTools Covered: Power BI Service, Power BI Desktop13
- 50.1Introduction to Power BI Publishing and Sharing Options
- 50.2Overview of Different Sharing Methods
- 50.3Publishing Reports from Power BI Desktop
- 50.4Publishing Reports to the Web
- 50.5Sharing Dashboards with Power BI Service
- 50.6Creating and Managing Workspaces and Apps (Power BI Pro)
- 50.7Using Content Packs (Power BI Pro)
- 50.8Printing or Saving Reports as PDFs
- 50.9Implementing Row-Level Security (Power BI Pro)
- 50.10Exporting Data from Visualizations
- 50.11Publishing Reports for Mobile Applications
- 50.12Exporting Reports to PowerPoint
- 50.13Summary of Sharing Options
- Module 51: Data Refresh and Gateway SetupTools Covered: Power BI Service, On-Premises Gateway5
- Module 52: Power BI and Excel IntegrationTools Covered: Power BI Desktop, Power BI Service, Excel5
- Module 53: Power BI Projects and Interview PreparationTools Covered: Power BI Desktop, Power BI Service4
- Module 54: Introduction to Tableau and BI ConceptsTableau Mastery (Optional**): Data Visualization and Business Intelligence6
- 54.1Overview of Data Warehousing and Business Intelligence
- 54.2Fundamentals of Data Analysis and Visualization
- 54.3Business Reporting and Dashboard Essentials
- 54.4Introduction to Tableau and Its Architecture
- 54.5Understanding Measures vs. Dimensions
- 54.6Continuous vs. Discrete Data, Value & Category Axes
- Module 55: Connecting and Managing Data Sources4
- Module 56: Saving and Publishing Workbooks3
- Module 57: Core Data Visualization Techniques5
- Module 58: Creating Effective VisualizationsBuilding Various Chart Types:6
- Module 59: Advanced Features and Analytics7
- 59.1Designing Interactive Dashboards
- 59.2Forecasting and Trend Analysis
- 59.3Adding Reference Lines, Bands, and Visual Highlights
- 59.4Handling Missing Values and Null Data
- 59.5Implementing Table Calculations and Totals
- 59.6Custom Formatting, Annotations, and Layout Adjustments
- 59.7Using Dashboard Actions: Filters and Highlights
- Module 60: Tableau Server and Collaboration4
- Module 61: Project Work and Interview PreparationNote- Students can choose Power BI or Tableau. Opting for both may result in a revised fee structure. Contact us for details.3




