Data Analytics Course in Noida with 100% Placement Assistance

Our data analytics course in Noida, in Sector 2, teaches Python, SQL, Power BI, and Tableau on real datasets, not slide decks. You’ll clean messy data, build dashboards, and run the same analysis a working analyst runs on day one.

Beginners and working professionals both join this program. Either way, you leave with a project portfolio, a certificate, and 100% placement assistance that runs until you’re placed, not until the course ends.

Certification Partners

Our Students Placed In These Companies

Data Analytics with AI Course Syllabus

ADVANCE PYTHON PROGRAMMING

1. Introduction to Python

Simple
Open Source
High Level Programming
Portable
Object and Procedure Oriented
Easy to Maintain

2. Input and Output Functions

The Input() function
The print() function

n use of % percent operator

n use of format()

3. Variable and Data Types

What is a Variable
Assign Values to variable
Typecasting
Data Types in Python

n Numeric

n String

n Boolean

n Componup

n List

n Tuple

n Set

n FrozenSet

n Dictionary

4. Operators in Python

Types of Operators

n Arithmetic Operators

n Comparison Operators

n Assignment Operators

n Logical Operators

n Bitwise Operators

n Identity Operators

n Membership Operators

n Operators Associativity

n Operator Precedence

n BEDMAS

5. Conditional Statements in Python

The if Statement
if- else statement
The elif Statement
Nested if-else ladder

6. Loops in Python

Use of while loop
use of for loop
range) function
arange) function
The break Statement
The continue Statement
The pass statement

7. User defined functions in python

Define a function
calling a function
Types of function
UDF
Function Arguments
Functions Parameters
Anonymous Function
Global and Local Variable
lambda
map
reduce
Filter
Mathematical Function
Trigonometric Function
Random Function

8. Strings in python

creating strings
difference between “” &”
creating multiline comment
basic string operations
creating slices in strings
String Built-in Functions
n capitalize()
n upper()
n lower()
n isalnum()
n isalpha()
n isnumeric()
n isdecimal()
n islower()
n isupper()

9. List

Access List items
Change List items
Add List Items
Remove List Items
Loop List
List Comprehension
Copy List
Join List
List built-in Method
n append()
n count()
n extend()
nreverse()
n sort()

10. Tuple

Access Tuples
Update Tuples
UnpackTuples
LoopTuple
JoinTuples
Tuplebuilt-in Methods
n index()
n count()

11. Sets

Create Sets
Access Set items
Add Set items
Remove Set items
Loop Sets
Join Sets

12. Dictionaries

Create Dictionaries
Access Dictionary items
Change Dictionary items
Add Dictionary items
Remove Dictionary items
Loop Dictionaries
Copy Dictionaries
Nested Dictionaries
Dictionary built-in Methods
n keys()
n values()
n items()
n get()

13. Python Modules

Date Module
Time Module
os Module
The import statement
The from…import Statement

ITERATORS- GENERATORS

PYTHON AND DATA ANALYTICS LIBRARY

Introduction to Advance EXCEL

Referencing, Named ranges,Uses, Arithemetic Functions

Logical functions

Referring data from different tables: Various types of Lookup, Nested IF

Advanced functions

Date and Text Functions

Data Handling::Data cleaning, Data type identification, Remove Duplicates, Formatting and Filtering

Data Visualization: Conditional Formatting, Charts

what if Analysis?

Data Summarization: Pivot Report and Charts

Data Summarization: Dashboard Creation, Tips and Tricks

Connecting to Data: Power Query, Pivot, Power Pivot within Excel

Introduction to SQL

SQL Commands and Data Types

DQL & Operators

Case When Then and Handling NULL Values

Group Operations & Aggregate Functions

Constraints

Joins

DDL

DML & TCL Commands

Indexes and Views

Stored Procedures

Function, Constructs

Union, Intersect, Sub-query

Exception Handling

Triggers

Power BI Introduction and Installation

The Power BI user interface, including types of data sources and visualizations

Sample dashboard with Animation Visual

Power BI Visualization

Power Query Editor

Modelling with Power BI

Power Query Editor Filter Data

Customize the data in Power BІ

Dax Expressions

Custom Visual

Power BI Service

Descriptive Statistics

Probability and Normal Distribution

Inferential Statistics

Data cleaning and Insights

Al Tools for Data Analytics & Visualization

DATA ANALYTICS PROJECTS:

ADVANCE PYTHON PROGRAMMING

1. Introduction to Python

Simple
Open Source
High Level Programming
Portable
Object and Procedure Oriented
Easy to Maintain

2. Input and Output Functions

The Input() function
The print() function

n use of % percent operator

n use of format()

3. Variable and Data Types

What is a Variable
Assign Values to variable
Typecasting
Data Types in Python

n Numeric

n String

n Boolean

n Componup

n List

n Tuple

n Set

n FrozenSet

n Dictionary

4. Operators in Python

Types of Operators

n Arithmetic Operators

n Comparison Operators

n Assignment Operators

n Logical Operators

n Bitwise Operators

n Identity Operators

n Membership Operators

n Operators Associativity

n Operator Precedence

n BEDMAS

5. Conditional Statements in Python

The if Statement
if- else statement
The elif Statement
Nested if-else ladder

6. Loops in Python

Use of while loop
use of for loop
range) function
arange) function
The break Statement
The continue Statement
The pass statement

7. User defined functions in python

Define a function
calling a function
Types of function
UDF
Function Arguments
Functions Parameters
Anonymous Function
Global and Local Variable
lambda
map
reduce
Filter
Mathematical Function
Trigonometric Function
Random Function

8. Strings in python

creating strings
difference between “” &”
creating multiline comment
basic string operations
creating slices in strings
String Built-in Functions
n capitalize()
n upper()
n lower()
n isalnum()
n isalpha()
n isnumeric()
n isdecimal()
n islower()
n isupper()

9. List

Access List items
Change List items
Add List Items
Remove List Items
Loop List
List Comprehension
Copy List
Join List
List built-in Method
n append()
n count()
n extend()
nreverse()
n sort()

10. Tuple

Access Tuples
Update Tuples
UnpackTuples
LoopTuple
JoinTuples
Tuplebuilt-in Methods
n index()
n count()

11. Sets

Create Sets
Access Set items
Add Set items
Remove Set items
Loop Sets
Join Sets

12. Dictionaries

Create Dictionaries
Access Dictionary items
Change Dictionary items
Add Dictionary items
Remove Dictionary items
Loop Dictionaries
Copy Dictionaries
Nested Dictionaries
Dictionary built-in Methods
n keys()
n values()
n items()
n get()

13. Python Modules

Date Module
Time Module
os Module
The import statement
The from…import Statement

ITERATORS- GENERATORS

PYTHON AND DATA ANALYTICS LIBRARY

Introduction to Advance EXCEL

Referencing, Named ranges,Uses, Arithemetic Functions

Logical functions

Referring data from different tables: Various types of Lookup, Nested IF

Advanced functions

Date and Text Functions

Data Handling::Data cleaning, Data type identification, Remove Duplicates, Formatting and Filtering

Data Visualization: Conditional Formatting, Charts

what if Analysis?

Data Summarization: Pivot Report and Charts

Data Summarization: Dashboard Creation, Tips and Tricks

Connecting to Data: Power Query, Pivot, Power Pivot within Excel

Introduction to SQL

SQL Commands and Data Types

DQL & Operators

Case When Then and Handling NULL Values

Group Operations & Aggregate Functions

Constraints

Joins

DDL

DML & TCL Commands

Indexes and Views

Stored Procedures

Function, Constructs

Union, Intersect, Sub-query

Exception Handling

Triggers

Power BI Introduction and Installation

The Power BI user interface, including types of data sources and visualizations

Sample dashboard with Animation Visual

Power BI Visualization

Power Query Editor

Modelling with Power BI

Power Query Editor Filter Data

Customize the data in Power BІ

Dax Expressions

Custom Visual

Power BI Service

Introduction to Tableau

Basic Charts & Formatting

Filters

Calculations

Data Combining Techniques

Custom Charts

Groups, Bins, Hierarchies, Sets, Parameters

Analytics & Dashboard

Dashboard Actions & Tableau Public

Descriptive Statistics

Probability and Normal Distribution

Inferential Statistics

Data cleaning and Insights

Al Tools for Data Analytics & Visualization

DATA ANALYTICS PROJECTS:

Enquiry Now

Our Placed Students

Tools That You will Learn

Excel

SQL

Power BI

Numpy

Pandas

Matplotlib

Seaborn

Jupyter

Julius

Colab

Claude

ChatGPT

Tableau

Copilot

25+ Data Analytics Skills You Will Learn

Data Cleaning
Data Collection
Data Wrangling
Data Analysis
Data Visualization
Statistical Analysis
Exploratory Data Analysis (EDA)
Report Generation
Business Intelligence (BI)
Dashboard Creation
Data Interpretation
Data Validation
Predictive Analytics
Data Storytelling
KPI Analysis
Problem Solving
Critical Thinking
Business Analysis
Data-Driven Decision Making
Requirement Analysis
Trend Analysis
Customer Analytics
Financial Analytics
Sales Analytics
Marketing Analytics

Our Process

What data analytics actually means

If you’re comparing data analytics courses in Noida right now, start with the basics. Data analytics is the process of cleaning, structuring, and interpreting data so a business can make a decision instead of a guess. A retail chain uses it to find out which store is losing money. A hospital uses it to predict bed occupancy next week. A bank uses it to catch fraud before a transaction clears.

None of that needs a PhD. It needs SQL to pull the data, Excel or Python to clean it, and a BI tool like Power BI or Tableau to make it readable for someone who isn’t a data person. That’s the job, in practice.

Companies across Noida and the wider NCR, from IT services firms to fintech startups, hire for exactly this skill set. Every team that touches a spreadsheet eventually needs someone who can turn it into an answer, and that demand isn’t slowing down.

Why train with Appwars Technologies

We’ve run data analytics batches in Noida for years, and it shows in how the course is built. Every instructor has worked as an analyst or BI developer before teaching, so the syllabus reflects what a hiring manager tests for, not just what fits neatly into a slide.

Batches stay small: 15 students, offline and online, taught live by the same instructor, so nobody gets lost in a recorded video queue.

You’ll work in the tools a working analyst opens every day: Excel, SQL, Python, Power BI, and Tableau, on lab machines in our Sector 2 center. Every project mirrors a real business problem: a sales dashboard, an HR attrition report, or a supply chain bottleneck, not a toy dataset from a textbook.

How the course is structured

The program runs 5 or 6 months, in two stages.

Stage one covers the fundamentals: Python programming, Excel from formulas through Power Query, and SQL from SELECT statements through window functions and stored procedures.

Stage two moves into the tools that turn raw numbers into a dashboard someone can act on: Power BI, DAX, and Tableau, plus a statistics module covering hypothesis testing, probability, and the AI tools (ChatGPT, Claude, and Julius AI) analysts now use to speed up reporting.

The full module-by-module syllabus is above. Every stage ends with a project you can put on your résumé.

The projects you’ll actually build

You won’t just watch us build dashboards. You’ll build seven of your own: a sales dashboard, an HR dashboard, a finance dashboard, an e-commerce dashboard, a supply chain dashboard, an employee database analysis, and a retail sales analysis.

Each one uses a dataset close to what you’d see on the job: messy, incomplete, and in need of real cleaning before it’s useful. A tutorial dataset that’s already clean teaches you nothing about the first two hours of a real analyst’s day.

By the time you finish, you’ll have a portfolio you can walk an interviewer through, not just a certificate. For more project ideas to practice on your own, see our guide to the top data analytics projects for your résumé.

Career paths and salary after the course

Graduates move into roles like Data Analyst, Business Intelligence Analyst, Reporting Analyst, and, with more experience, Data Scientist or Data Engineer. IT services firms, fintech, e-commerce, and healthcare companies across Delhi NCR hire for all four.

Pay depends heavily on your tool stack, not just your job title. A fresher who knows only Excel starts near the bottom of the range. A fresher who can show SQL, Python, and 2 to 3 real dashboard projects starts meaningfully higher.

We break down the exact numbers, by experience level and city, in our data analyst salary guide. Use it to check any job offer against real market data instead of a course brochure’s promise.

Where our students land

Our placement team works with companies across IT services, product, and fintech to place data analytics graduates in the roles they trained for: Data Analyst, Business Intelligence Analyst, and reporting roles at MNCs and growing startups across the NCR.

Placement support runs until you’re placed, not until the course ends. That includes mock interviews, résumé reviews built around ATS scoring, and introductions to our hiring partners.

See our full placements page for the companies recent batches have joined.

How to enroll

No degree or coding background is required. Basic comfort with Excel helps, but the course starts from the fundamentals either way.

Fill out the enquiry form on this page or call +91 9911169001.
Our academic counsellor walks you through batch timing, fees, and the 5 or 6 month options, and answers any syllabus questions.
Pick your batch and confirm your seat. Batches run small (15 students), so seats fill fast once a batch opens.

Check upcoming batch dates for the next start date, offline or online.

Support that continues after class

Every batch gets an internship certificate for the hands-on project work, on top of the course completion certificate.

You also get study material, recorded sessions for revision, and access to instructors after the batch ends if a concept needs a second look. Mentors have worked as analysts and BI developers, so questions get answered by someone who’s done the job, not just taught it.

Career support runs on the same timeline as placement: resume building, mock interviews, and referrals to hiring partners, for as long as it takes to land a role.

Who this course is for

Graduates in any stream (B.E, B.Tech, MCA, BCA, B.Com) who want a career in data analytics or business intelligence
IT professionals looking to move into an analytics or BI-focused role
Professionals from non-IT backgrounds making a switch into tech
Anyone restarting their career after a gap
Working professionals who want to add Power BI, Tableau, or SQL to an existing skill set

Get Certified to boost your Professional Growth

Recognition Across the Globe

Globally accepted certification to showcase expertise and unlock career opportunities.

Guaranteed Validity for Life

Lifetime-valid certificate ensures lasting credibility and career-long professional recognition.

Special Opportunities for Networking

Join expert community, collaborate, and grow through valuable networking opportunities.

Student Testimonials

      EXCELLENT  
   Based on 1244 reviews 
    
 
 
 
   
 
 
       Posted on Google  
   
   Deepali Sharma 
 
 
 
 Trustindex verifies that the original source of the review is Google. Had a great learning experience. Thanks to Priyanshu Pal sir for sharing his valuable knowledge. I got to know about AI, Data Science, Prompt Engineering and different fields of technology.
  
 
      Posted on Google  
   
   Ramkaran Singh Chauhan 
 
 
 
 Trustindex verifies that the original source of the review is Google. It was a great session and experience with "Priyanshu Pal Sir" at Industrial Visit.
  
 
      Posted on Google  
   
   Abhishek Gupta 
 
 
 
 Trustindex verifies that the original source of the review is Google. Very good and clean learning environment with good faculty Priyanshu pal sir he is very good explainer of knowledge.
  
 
      Posted on Google  
   
   Anand Raj 
 
 
 
 Trustindex verifies that the original source of the review is Google. Learned about ai/ml , data science and python frameworks overview from Priyanshu sir
  
 
      Posted on Google  
   
   Praanjali 
 
 
 
 Trustindex verifies that the original source of the review is Google. It was a great experience under the guidance of priyanshu pal.
  
 
      Posted on Google  
   
   Pushkar Maity 
 
 
 
 Trustindex verifies that the original source of the review is Google. Very motivational and futuristic examples for our future and nature of all faculty is also good
  
 
      Posted on Google  
   
   Siya Tanwar 
 
 
 
 Trustindex verifies that the original source of the review is Google. I had a great experience with the Appwars Technologies especially with Priyanshu Sir. Their way of explaining was wonderful and I liked every bit of it.
  
 
      Posted on Google  
   
   Muskan Yadav 
 
 
 
 Trustindex verifies that the original source of the review is Google. Had a great learning session with priyanshu sir and Appwars technology. Great person and mentor!
  
 
  
  
 
     Verified by Trustindex  Trustindex verified badge is the Universal Symbol of Trust. Only the greatest companies can get the verified badge who has a review score above 4.5, based on customer reviews over the past 12 months. Read more

Frequently Asked Questions

What is Data Analytics and why should I learn it?

Data analytics means examining data to draw conclusions and support decisions. It's in demand across finance, healthcare, marketing, and IT, and the skill transfers across all of them.

Why choose Appwars Technologies for a data analytics course in Noida?

Industry-experienced mentors, small batches, real projects instead of textbook exercises, and placement support that runs until you're placed, not until the course ends.

What are the prerequisites for enrolling?

None are required. Basic familiarity with Excel or statistics helps, but the course starts from the fundamentals and builds up from there.

What tools and technologies will I learn?

You will learn Microsoft Excel (advanced), SQL and MySQL, Power BI and Tableau, Python for data analysis, NumPy, Pandas, and Matplotlib, Machine learning basics and Data cleaning and visualization techniques

Will I get placement support after training?

Yes. Support includes resume building, mock interviews, and referrals to hiring partners, and it continues until you're placed.

Is there a data analytics course in Noida with placement assistance?

Yes. This course includes 100% placement assistance: resume building, mock interviews, and direct referrals to our hiring partners, continuing until you land a role.

What are the data analytics course fees in Noida?

₹41,300 for the 5-month track and ₹48,000 for the 6-month track, at current batch pricing. Both include live instruction, hands-on projects, and placement support.

Is this course available offline, online, or both?

Both. Classes run offline at our Sector 2 center in Noida and Greater Noida and live online for students who can't attend in person.

Where is the Appwars Technologies data analytics institute in Noida?

C-20, 1st Floor, Noida Sector 2, U.P. 201301, near Nirula's Hotel and Noida Sector 15 Metro.

What's the difference between this course and the Data Science course?

This course focuses on analyzing existing data: cleaning, visualization, dashboards, and reporting with Excel, SQL, Power BI, and Tableau. The Data Science course goes further into machine learning and model building. Most working analysts start here and move into data science later if the role calls for it.

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Data Analytics Course in Noida with 100% Placement Assistance

Certification Partners

Our Students Placed In These Companies

Data Analytics with AI Course Syllabus

ADVANCE PYTHON PROGRAMMING

1. Introduction to Python

2. Input and Output Functions

3. Variable and Data Types

4. Operators in Python

5. Conditional Statements in Python

6. Loops in Python

7. User defined functions in python

8. Strings in python

9. List

10. Tuple

11. Sets

12. Dictionaries

13. Python Modules

ITERATORS- GENERATORS

Object Oriented Programming

PYTHON AND DATA ANALYTICS LIBRARY

1. NumPУ

2. Pandas

3. Matplotlib

4. Seaborn

5. WEB SCRAPING

Introduction to Advance EXCEL

Referencing, Named ranges,Uses, Arithemetic Functions

Logical functions

Referring data from different tables: Various types of Lookup, Nested IF

Advanced functions

Date and Text Functions

Data Handling::Data cleaning, Data type identification, Remove Duplicates, Formatting and Filtering

Data Visualization: Conditional Formatting, Charts

what if Analysis?

Data Summarization: Pivot Report and Charts

Data Summarization: Dashboard Creation, Tips and Tricks

Connecting to Data: Power Query, Pivot, Power Pivot within Excel

Connecting to Data: Power Query, Pivot, Power Pivot within Excel

Introduction to SQL

SQL Commands and Data Types

DQL & Operators

Case When Then and Handling NULL Values

Group Operations & Aggregate Functions

Constraints

Joins

DDL

DML & TCL Commands

Indexes and Views

Stored Procedures

Function, Constructs

Union, Intersect, Sub-query

Exception Handling

Triggers

Power BI Introduction and Installation

The Power BI user interface, including types of data sources and visualizations

Sample dashboard with Animation Visual

Power BI Visualization

Power Query Editor

Modelling with Power BI

Power Query Editor Filter Data

Customize the data in Power BІ

Dax Expressions

Custom Visual

Power BI Service

Descriptive Statistics

Probability and Normal Distribution

Inferential Statistics

Data cleaning and Insights

Al Tools for Data Analytics & Visualization

DATA ANALYTICS PROJECTS:

ADVANCE PYTHON PROGRAMMING

1. Introduction to Python

2. Input and Output Functions

3. Variable and Data Types

4. Operators in Python

5. Conditional Statements in Python

6. Loops in Python

7. User defined functions in python

8. Strings in python