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Are you Looking for the Best Institute for Data Analytics using Python training in Noida?

DUCAT offers Data Analytics using Python training classes with live projects by expert trainers in Noida.

Our Data Analytics using Python training program in Noida is specially designed for Under-Graduates (UG), Graduates, working professionals, and also for Freelancers.

We provide end-to-end learning on Data Analytics using Python Domain with deeper dives for creating a winning career for every profile.

If you are looking for a high-quality analytics training program that will give you the skills you need to succeed in the real world, then Ducat The IT Training School is the perfect place.

Contact Ducat at 70-70-90-50-90 for more about their excellent job-oriented analytics training program.

Why learn Data Analytics using Python?

It's continued to be a great option for data scientists who use it for building Machine learning applications or using them and other scientific computations.

Data Analytics Using Python Training in Noida cuts development time in half with its simple-to-read syntax and easy compilation feature with the easy-to-learn concept.

Debugging any type of program is a breeze in this language with its built-in debugger.

It runs on every famous type of platform like Windows, Linux/Unix, and Mac OS and has been ported to Java and .NET virtual machines.

Python is free to use language, even for commercial products, because of its OSI-approved open-source license, so anyone can use it for free.

It has been opted as the most preferred Language for Data Analytics and the increasing search trends on Python every day also indicates that it is the "Next Big Thing" and a must for aspirants in the Data Analytics field.

Analytics Training Institute


The capacity to extract actionable insights from enormous amounts of data has become essential for businesses across industries in today's data-driven environment.

This growing demand for skilled data analysts and professionals has led numerous analytics training institutes to emerge.

One such institute that stands out is Ducat, The IT Training School, known for its comprehensive and industry-focused analytics programs.

The vast range of courses offered by Analytics Training Institute is created to give students the knowledge and skills they need to succeed in data analytics.

The institute addresses various issues, from fundamental ideas to cutting-edge methods, including data visualization, statistical analysis, machine learning, predictive modeling, and more.

The curriculum is carefully crafted to meet the evolving industry demands and ensure learners are well-prepared to tackle real-world analytics challenges.

There are many different analytics training institutes available, but not all of them are almost created equal.

Ducat, The IT Training School, is one of India's leading analytics training institutes, having a physical presence in Delhi, Noida, Gurgaon and Ghaziabad.

The institute's extensive curriculum covers all of the fundamental competencies needed for a career in analytics.

Analytics Training Importance

  1. Ducat's analytics training program is designed to help you develop the skills you need to succeed in the real world.
  2. The program includes hands-on training with real-world data sets so that you can apply your skills to real-world problems.
  3. In addition to the technical skills, Ducat also teaches you the soft skills essential for success in analytics. These skills include communication, teamwork, and problem-solving.
  4. Ducat's analytics training program is also highly practical. The program includes a capstone project, where you can apply your skills to a real-world problem.
  5. You will have the opportunity to show potential employers your talents through this project.
  6. Additionally, Ducat helps its learners find jobs.
  7. The institute has a strong network of corporate partners who are always looking for talented data analysts and scientists.
  8. With the help of Ducat, you can be confident that you can find a job after completing the program.

If you are serious about a career in analytics, I encourage you to be admitted to Ducat IT Training School.

The institute's comprehensive curriculum, hands-on training, and placement assistance will give you the skills and knowledge you need to succeed in this exciting field.

Benefits of training from Ducat

Here are some of the benefits of taking an analytics course at Ducat The IT Training School:

  • You will learn from Industry-experienced and qualified instructors who are experts in their respective fields.
  • You will have use of the updated tools and numerous applications.
  • Networking opportunities with academic and professional peers are available.
  • You will receive an Industry recognized course completion certificate.

Why To Enroll In Our Data Analytics Using Python Training Course in Noida?

We Focus on Innovative ideas, High-quality Training, Smart Classes, 100% job assistance, and Opening the doors of opportunities.

Our Data Analytics using Python Trainees are working across the nation. We at Ducat India, No#1 Data Analytics using Python Course in Noida with 100% Placement.

Certified Trainers with Over 10,000 Students Trained in Data Analytics using Python Course in Noida.

What Our Students Will Get During Data Analytics using Python Training Course?

Get dedicated student support, career services, industry expert mentors, and real-world projects. Career Counselling. Timely Doubt Resolution. 50% Salary Hike, Career Counselling Case Studies + Tools + Certificate.

Why Ducat?

Ducat has a dedicated team of highly expert trainers to identify, evaluate, implement, and provide the Best Data Analytics Using Python Training Institute in Noida for our students.

Our Trainers leverage a defined methodology that helps identify opportunities, develop the most optimal resolution and maturely execute the solution.

We have the best trainers across the world to provide Best Data Analytics Using Python Training in Noida who are highly qualified and are the best in their field.

The Training & Placement cell is committed to providing all attainable help to the students in their efforts to seek out employment and internships in every field.

The placement department works beside alternative departments as a team in molding the scholars to the necessities of varied industries.

We got proactive and business-clued-in Placement Cells that pride themselves on a robust skilled network across numerous sectors.

It actively coordinates with every student and ensures that they get placed with purported MNCs within six months of graduating. We are the Best Data Analytics Using Python Training Institute in Noida.

Introduction To Python

  • Why Python
  • Application areas of python
  • Python implementations
  • Cpython
  • Jython
  • Ironpython
  • Pypy
  • Python versions
  • Installing python
  • Python interpreter architecture
  • Python byte code compiler
  • Python virtual machine(pvm)

Writing and Executing First Python Program

  • Using interactive mode
  • Using script mode
  • General text editor and command window
  • Idle editor and idle shell
  • Understanding print() function
  • How to compile python program explicitly

Python Language Fundamentals

  • Character set
  • Keywords
  • Comments
  • Variables
  • Literals
  • Operators
  • Reading input from console
  • Parsing string to int, float

Python Conditional Statements

  • If statement
  • If else statement
  • If elif statement
  • If elif else statement
  • Nested if statement

Looping Statements

  • While loop
  • For loop
  • Nested loops
  • Pass, break and continue keywords

Standard Data Types

  • Int, float, complex, bool, nonetype
  • Str, list, tuple, range
  • Dict, set, frozenset

String Handling

  • What is string
  • String representations
  • Unicode string
  • String functions, methods
  • String indexing and slicing
  • String formatting

Python List

  • Creating and accessing lists
  • Indexing and slicing lists
  • List methods
  • Nested lists
  • List comprehension

Python Tuple

  • Creating tuple
  • Accessing tuple
  • Immutability of tuple

Python Set

  • How to create a set
  • Iteration over sets
  • Python set methods
  • Python frozenset

Python Dictionary

  • Creating a dictionary
  • Dictionary methods
  • Accessing values from dictionary
  • Updating dictionary
  • Iterating dictionary
  • Dictionary comprehension

Python Functions

  • Defining a function
  • Calling a function
  • Types of functions
  • Function arguments
  • Positional arguments, keyword arguments
  • Default arguments, non-default arguments
  • Arbitrary arguments, keyword arbitrary arguments
  • Function return statement
  • Nested function
  • Function as argument
  • Function as return statement
  • Decorator function
  • Closure
  • Map(), filter(), reduce(), any() functions
  • Anonymous or lambda function

Modules & Packages

  • Why modules
  • Script v/s module
  • Importing module
  • Standard v/s third party modules
  • Why packages
  • Understanding pip utility

File I/O

  • Introduction to file handling
  • File modes
  • Functions and methods related to file handling
  • Understanding with block

Regular Expressions(Regex)

  • Need of regular expressions
  • Re module
  • Functions /methods related to regex
  • Meta characters & special sequences


Introduction to Database

  • Database Concepts
  • What is Database Package?
  • Understanding Data Storage
  • Relational Database (RDBMS) Concept

SQL (Structured Query Language)

  • SQL basics
  • DML, DDL & DQL
  • DDL: create, alter, drop
  • SQL constraints:
  • Not null, unique
  • ,
  • Primary & foreign key, composite key
  • Check, default
  • DML: insert, update, delete and merge
  • DQL : select
  • Select distinct
  • SQL where
  • SQL operators
  • SQL like
  • SQL order by
  • SQL aliases
  • SQL views
  • SQL joins
  • Inner join
  • Left (outer) join
  • Right (outer) join
  • Full (outer) join
  • Mysql functions
  • String functions
  • Char_length
  • Concat
  • Lowe
  • r
  • Reverse
  • Uppe
  • r
  • Numeric functions
  • Max, min, sum
  • Avg, count, abs
  • Date functions
  • Curdate
  • Curtime●
  • Now

Statistics, Probability &Analytics:

Introduction to Statistics

  • Sample or population
  • Measures of central tendency
  • Arithmetic mean
  • Harmonic mean
  • Geometric mean
  • Mode
  • Quartile
  • First quartile
  • Second quartile(median)
  • Third quartile
  • Standard deviation

Probability Distributions

  • Introduction to probability
  • Conditional probability
  • Normal distribution
  • Uniform distribution
  • Exponential distribution
  • Right & left skewed distribution
  • Random distribution
  • Central limit theorem

Hypothesis Testing

  • Normality test
  • Mean test
  • T-test
  • Z-test
  • ANOVA test
  • Chi square test
  • Correlation and covariance

Numpy Package

  • Difference between list and numpy array
  • Vector and matrix operations
  • Array indexing and slicing

Pandas Package

Introduction to pandas

  • Labeled and structured data
  • Series and dataframe objects

How to load datasets

  • From excel
  • From csv
  • From html table

Accessing data from Data Frame

  • at &iat
  • loc&iloc
  • head() & tail()

Exploratory Data Analysis (EDA)

  • describe()
  • groupby()
  • crosstab()
  • boolean slicing / query

Data Manipulation & Cleaning

  • Map(), apply()
  • Combining data frames
  • Adding/removing rows & columns
  • Sorting data
  • Handling missing values
  • Handling duplicacy
  • Handling data error

Handling Date and Time

Data Visualization using matplotlib and seaborn packages

  • Scatter plot, lineplot, bar plot
  • Histogram, pie chart,
  • Jointplot, pairplot, heatmap
  • Outlier detection using boxplot

Advanced Excel

Advanced Excel Course - Overview of the Basics of Excel

  • Customizing common options in Excel
  • Absolute and relative cells
  • Protecting and un-protecting worksheets and cells

- Working with Functions

  • Writing conditional expressions (using IF)
  • Using logical functions (AND, OR, NOT)
  • Using lookup and reference functions (VLOOKUP, HLOOKUP, MATCH, INDEX)
  • VlookUP with Exact Match, Approximate Match
  • Nested VlookUP with Exact Match
  • VlookUP with Tables, Dynamic Ranges
  • Nested VlookUP with Exact Match
  • Using VLookUP to consolidate Data from Multiple Sheets

Advanced Excel Course - Data Validations

  • Specifying a valid range of values for a cell
  • Specifying a list of valid values for a cell
  • Specifying custom validations based on formula for a cell

Advanced Excel Course - Working with Templates

  • Designing the structure of a template
  • Using templates for standardization of worksheets

Advanced Excel Course - Sorting and Filtering Data

  • Sorting tables
  • Using multiple-level sorting
  • Using custom sorting
  • Filtering data for selected view (AutoFilter)
  • Using advanced filter options

Advanced Excel Course - Working with Reports

  • Creating subtotals
  • Multiple-level subtotals
  • Creating Pivot tables
  • Formatting and customizing Pivot tables
  • Using advanced options of Pivot tables
  • Pivot charts
  • Consolidating data from multiple sheets and files using Pivot tables
  • Using external data sources
  • Using data consolidation feature to consolidate data
  • Show Value As ( % of Row, % of Column, Running Total, Compare with Specific Field)
  • Viewing Subtotal under Pivot
  • Creating Slicers ( Version 2010 & Above)

Advanced Excel Course - More Functions

  • Date and time functions
  • Text functions
  • Database functions
  • Power Functions (CountIf, CountIFS, SumIF, SumIfS)

Advanced Excel Course - Formatting

  • Using auto formatting option for worksheets
  • Using conditional formatting option for rows, columns and cells

Advanced Excel Course - Macros

  • Relative & Absolute Macros
  • Editing Macro's

Advanced Excel Course - WhatIf Analysis

  • Goal Seek
  • Data Tables
  • Scenario Manager

Advanced Excel Course - Charts

  • Using Charts
  • Formatting Charts
  • Using 3D Graphs
  • Using Bar and Line Chart together
  • Using Secondary Axis in Graphs
  • Sharing Charts with PowerPoint / MS Word, Dynamically
  • (Data Modified in Excel, Chart would automatically get updated)

Advanced Excel Course - New Features Of Excel

  • Sparklines, Inline Charts, data Charts
  • Overview of all the new features

Advanced Excel Course - Final Assignment

  • The Final Assignment would test contains questions to be solved at the end of the Course


Create a Macro:

  • Swap Values, Run Code from a Module, Macro Recorder, Use Relative References,
  • FormulaR1C1, Add a Macro to the Toolbar, Macro Security, Protect Macro.


  • MsgBox Function, Input Box Function.

Workbook and Worksheet Object:

  • Path and Full Name, Close and Open, Loop through Books and Sheets, Sales Calculator, Files in a Directory, Import Sheets, Programming Charts.

Range Object:

  • Current Region, Dynamic Range, Resize, Entire Rows and Columns, Offset, From Active Cell to Last Entry, Union and Intersect, Test a Selection, Possible Football Matches, Font, Background Colors, Areas Collection, Compare Ranges.


  • Option Explicit, Variable Scope, Life of Variables.

If Then Statement:

  • Logical Operators, Select Case, Tax Rates, Mod Operator, Prime Number Checker, Find Second Highest Value, Sum by Color, Delete Blank Cells.


  • Loop through Defined Range, Loop through Entire Column, Do Until Loop, Step Keyword, Create a Pattern, Sort Numbers, Randomly Sort Data, Remove Duplicates, Complex Calculations, Knapsack Problem.

Macro Errors:

  • Debugging, Error Handling, Err Object, Interrupt a Macro, Macro Comments.

String Manipulation:

  • Separate Strings, Reverse Strings, Convert to Proper Case, Count Words.

Date and Time:

  • Compare Dates and Times, DateDif Function, Weekdays, Delay a Macro, Year Occurrences, Tasks on Schedule, Sort Birthdays.


  • Before DoubleClick Event, Highlight Active Cell, Create a Footer Before Printing, Bills and Coins, Rolling Average Table
  • .


  • Dynamic Array, Array Function, Month Names, Size of an Array.

Function and Sub:

  • User Defined Function, Custom Average Function, Volatile Functions, ByRef and ByVal.

Application Object:

  • Status Bar, Read Data from Text File, Write Data to Text File.

ActiveX Controls:

  • Text Box, List Box, Combo Box, Check Box, Option Buttons, Spin Button, Loan Calculator.

User form:

  • User form and Ranges, Currency Converter, Progress Indicator, Multiple List Box Selections, Multicolumn Combo Box, Dependent Combo Boxes, Loop through Controls, Controls Collection, User form with Multiple Pages, Interactive User form


Tableau - Home

  • Tableau - overview
  • Tableau - environment setup
  • Tableau - get started
  • Tableau - navigation
  • Tableau - design flow
  • Tableau - file types
  • Tableau - data types
  • Tableau - show me
  • Tableau - data terminology

Tableau - Data Sources

  • Tableau - custom data view
  • Tableau - data sources
  • Tableau - extracting data
  • Tableau - fields operations
  • Tableau - editing metadata
  • Tableau - data joining
  • Tableau - data blending

Tableau – Work Sheet

  • Tableau - add worksheets
  • Tableau - rename worksheet
  • Tableau - save & delete worksheet
  • Tableau - reorder worksheet
  • Tableau - paged workbook

Tableau – Calculation

  • Tableau - operators
  • Tableau - functions
  • Tableau - numeric calculations
  • Tableau - string calculations
  • Tableau - date calculations
  • Tableau - table calculations
  • Tableau - lod expressions

Tableau – Sorting & Filter

  • Tableau - basic sorting
  • Tableau - basic filters
  • Tableau - quick filters
  • Tableau - context filters
  • Tableau - condition filters
  • Tableau - top filters
  • Tableau - filter operations

Tableau - Charts

  • Tableau - bar chart
  • Tableau - line chart
  • Tableau – pie chart
  • Tableau - crosstab
  • Tableau - scatter plot
  • Tableau - bubble chart
  • Tableau - bullet graph
  • Tableau - box plot
  • Tableau - tree map
  • Tableau - bump chart
  • Tableau - gantt chart
  • Tableau - histogram
  • Tableau - motion charts
  • Tableau - waterfall charts
  • Tableau - dashboard


  • One project using python &sql
  • One dashboard using tableau
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