DATA ANALYTICS USING PYTHON TRAINING IN Jaipur | DATA ANALYTICS WITH PYTHON

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

Groot Academy offers Data Analytics using Python training classes with live projects by expert trainers in Jaipur.

Our Data Analytics using Python training program in Jaipur is specially designed for Undergraduates (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, thenGroot-Academy The IT Training School is the perfect place. Contact Groot-Academy at 8690047091 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 Jaipur 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 indicate that it is the "Next Big Thing" and a must for aspirants in the Data Analytics field.

Important: Analytics Training Institute

Introduction

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 isGroot-Academy, 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 modelling, 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 created equal.

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

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

Analytics Training Importance

Groot's analytics training program is designed to help you develop the skills you need to succeed in the real world.

The program includes hands-on training with real-world data sets so that you can apply your skills to real-world problems.

In addition to the technical skills,Groot-Academy also teaches you the soft skills essential for success in analytics. These skills include communication, teamwork, and problem-solving.

Groot'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.

You will have the opportunity to show potential employers your talents through this project.

Additionally,Groot-Academy helps its learners find jobs.

The institute has a strong network of corporate partners who are always looking for talented data analysts and scientists.

With the help ofGroot-Academy, 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 toGroot-Academy 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 fromGroot-Academy

Here are some of the benefits of taking an analytics course atGroot-Academy 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-recognised course completion certificate.

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

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 atGroot-Academy India, The #1 Data Analytics using Python Course in Jaipur with 100% Placement.

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

Why Groot-Academy?

  • Groot has a dedicated team of highly expert trainers to identify, evaluate, implement, and provide the Best Data Analytics Using Python Training Institute in Jaipur 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 the Best Data Analytics Using Python Training in Jaipur 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 moulding the scholars to the necessities of varied industries.
  • We have 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 Jaipur.

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 To Enrol In Our Mern Stack Training Course in Jaipur?

We Focus on Innovative ideas, High-quality Training, Smart Classes, 100% job assistance, and Opening the doors of opportunities. Our Mern Stack Trainees are working across the nation. We at Groot Academy India, No#1 Mern Course in Jaipur with 100% Placement. Certified Trainers with Over 10,000 Students Trained in Online Mern Stack Course in Jaipur.

ENROOL NEW
Key Takeaways: Mern stack developers can efficiently build web and mobile applications using standard processes and abilities. It implements design thinking with enhanced expertise in various technologies. In the coming years, MERN Stack is highly likely to be used extensively since more and more applications are now built-in in JavaScript.

Reasons To Choose Groot Academy For Mern Stack Developer

Frequently Asked MERN Course Interview Questions

1:What is the difference between structured and unstructured data in the context of data analytics?

Ans: Structured data is organized and easily searchable (e.g., databases), while unstructured data lacks a predefined data model and includes things like text, images, and videos.

2: How does data analytics contribute to decision-making processes?

Ans: Data analytics provides evidence-based insights, reducing uncertainty and supporting more informed decision-making across various domains such as business, healthcare, and government.

3:What is the role of data preprocessing in data analytics?

Ans:Data preprocessing involves cleaning and transforming raw data into a format suitable for analysis. It includes handling missing values, outliers, and normalization to enhance the quality of the data.

4: What are some popular tools and technologies used in data analytics?

Ans: Tools like Python, R, SQL, and platforms like Apache Hadoop and Apache Spark are commonly used. Visualization tools such as Tableau and Power BI are also popular for presenting insights.

5: How is data analytics applied in healthcare?

Ans:In healthcare, data analytics is used for patient outcome predictions, disease diagnosis, resource optimization, and identifying trends to improve overall healthcare delivery.

6: What is the role of a data analyst vs. a data scientist?

Ans:Data analysts focus on analyzing and interpreting data to answer specific questions, while data scientists use advanced statistical and machine learning techniques to uncover patterns and insights, often involving more complex and unstructured data.

7: How does data analytics contribute to cybersecurity?

Ans:Data analytics helps in identifying patterns indicative of cyber threats, detecting anomalies in network behavior, and enhancing overall security by predicting and preventing potential breaches.

8:What are the challenges of implementing a data-driven culture in an organization?

Ans:Challenges include resistance to change, lack of data literacy, data silos within the organization, and the need for strong leadership support to foster a culture that values data-driven decision-making.

9:What is the concept of A/B testing in data analytics?

Ans:A/B testing, also known as split testing, involves comparing two versions (A and B) of a webpage, app, or other elements to determine which performs better. It is commonly used in marketing and product development.

10:How can businesses address the issue of bias in data analytics models?

Ans:Businesses can address bias by ensuring diverse and representative datasets, regularly auditing models for fairness, and promoting transparency in the development and deployment of machine learning algorithms.

Course content

Introduction to Statistical Analysis

  • Counting, Probability, and Probability Distributions
  • Sampling Distributions
  • Estimation and Hypothesis Testing
  • Scatter Diagram
  • Anova and Chisquare
  • Imputation Techniques
  • Data Cleaning
  • Correlation and Regression

Introduction to Data Analytics

  • Data Analytics Overview
  • Importance of Data Analytics
  • Types of Data Analytics
  • Descriptive Analytics
  • Diagnostic Analytics
  • Predictive Analytics
  • Prescriptive Analytics
  • Benefits of Data Analytics
  • Data Visualization for Decision Making
  • Data Types, Measure Of central tendency, Measures of Dispersion
  • Graphical Techniques, Skewness & Kurtosis, Box Plot
  • Descriptive Stats
  • Sampling Funnel, Sampling Variation, Central Limit Theorem, Confidence interval

Basics to Advanced

  • Excel tutorial
  • Text to Columns
  • Concatenate
  • The Concatenate Function
  • The Right Function with Concatenation
  • Absolute Cell References
  • Data Validation
  • Time and Date Calculations
  • Conditional Formatting
  • Exploring Styles and Clearing Formatting
  • Using Conditional Formatting to Hide Cells
  • Using the IF Function
  • Changing the “Value if false” Condition to Text
  • Pivot Tables
  • Creating a Pivot Table
  • Specifying PivotTable Data
  • Changing a PivotTables Calculation
  • Filtering and Sorting a PivotTable
  • Creating a PivotChart
  • Grouping Items
  • Updating a PivotTable
  • Formatting a PivotTable
  • Using Slicers
  • Charts
  • Creating a Simple Chart
  • Charting Non-Adjacent Cells
  • Creating a Chart Using the Chart Wizard
  • Modifying Charts
  • Moving an Embedded Chart
  • Sizing an Embedded Chart
  • Changing the Chart Type
  • Chart Types
  • Changing the Way Data is Displayed
  • Moving the Legend
  • Formatting Charts
  • Adding Chart Items
  • Formatting All Text
  • Formatting and Aligning Numbers
  • Formatting the Plot Area
  • Formatting Data Markers
  • Pie Charts
  • Creating a Pie Chart
  • Moving the Pie Chart to its Own Sheet
  • Adding Data Labels
  • Exploding a Slice of a Pie Chart
  • Data Analysis − Overview
  • types of Data Analysis
  • Data Analysis Process
  • Working with Range Names
  • Copying Name using Formula Autocomplete
  • Range Name Syntax Rules
  • Creating Range Names
  • Creating Names for Constants
  • Managing Names
  • Scope of a Name
  • Editing Names
  • Applying Names
  • Using Names in a Formula
  • Viewing Names in a Workbook
  • Copying Formulas with Names
  • Difference between Tables and Ranges
  • Create Table
  • Table Name
  • Managing Names in a Table
  • Table Headers replacing Column Letters
  • Propagation of a Formula in a Table
  • Resize Table
  • Remove Duplicates
  • Convert to Range
  • Table Style Options
  • Table Styles
  • Cleaning Data with Text Functions
  • Removing Unwanted Characters from Text
  • Extracting Data Values from Text
  • Formatting Data with Text Functions
  • Date Formats
  • Conditional Formatting
  • Sorting
  • Filtering
  • Lookup Functions
  • Pivoting

SQL

  • Introduction to Oracle Database
  • Retrieve Data using the SQL SELECT Statement
  • Learn to Restrict and Sort Data
  • Usage of Single-Row Functions to Customize Output
  • Invoke Conversion Functions and Conditional Expressions
  • Aggregate Data Using the Group Functions
  • Display Data from Multiple Tables Using Joins
  • Use Sub-Queries to Solve Queries
  • The SET Operators
  • Data Manipulation Statements
  • Use of DDL Statements to Create and Manage Tables
  • Other Schema Objects
  • Control User Access
  • Management of Schema Objects
  • Manage Objects with Data Dictionary Views
  • Manipulate Large Data Sets
  • Data Management in Different Time Zones
  • Retrieve Data Using Sub-queries
  • Regular Expression Support

Tableau Course Material

  • Start Page
  • Show Me
  • Connecting to Excel Files
  • Connecting to Text Files
  • Connect to Microsoft SQL Server
  • Connecting to Microsoft Analysis Services
  • Creating and Removing Hierarchies
  • Bins
  • Joining Tables
  • Data Blending

Learn Tableau Basic Reports

  • Parameters
  • Grouping Example 1
  • Grouping Example 2
  • Edit Groups
  • Set
  • Combined Sets
  • Creating a First Report
  • Data Labels
  • Create Folders
  • Sorting Data
  • Add Totals, Sub Totals and Grand Totals to Report

Learn Tableau Charts

  • Area Chart
  • Bar Chart
  • Box Plot
  • Bubble Chart
  • Bump Chart
  • Bullet Graph
  • Circle Views
  • Dual Combination Chart
  • Dual Lines Chart
  • Funnel Chart
  • Traditional Funnel Charts
  • Gantt Chart
  • Grouped Bar or Side by Side Bars Chart
  • Heatmap
  • Highlight Table
  • Histogram
  • Cumulative Histogram
  • Line Chart
  • Lollipop Chart
  • Pareto Chart
  • Pie Chart
  • Scatter Plot
  • Stacked Bar Chart
  • Text Label
  • Tree Map
  • Word Cloud
  • Waterfall Chart

Learn Tableau Advanced Reports

  • Dual Axis Reports
  • Blended Axis
  • Individual Axis
  • Add Reference Lines
  • Reference Bands
  • Reference Distributions
  • Basic Maps
  • Symbol Map
  • Use Google Maps
  • Mapbox Maps as a Background Map
  • WMS Server Map as a Background Map

Learn Tableau Calculations & Filters

  • Calculated Fields
  • Basic Approach to Calculate Rank
  • Advanced Approach to Calculate Ra
  • Calculating Running Total
  • Filters Introduction
  • Quick Filters
  • Filters on Dimensions
  • Conditional Filters
  • Top and Bottom Filters
  • Filters on Measures
  • Context Filters
  • Slicing Fliters
  • Data Source Filters
  • Extract Filters

Learn Tableau Dashboards

  • Create a Dashboard
  • Format Dashboard Layou
  • Create a Device Preview of a Dashboard
  • Create Filters on Dashboard
  • Dashboard Objects
  • Create a Story
  • Tableau online.
  • Overview of Tableau Server.
  • Publishing Tableau objects and scheduling/subscription

Introduction to Power BI

  • Get Started with Power BI
  • Overview: Power BI concepts
  • Sign up for Power BI
  • Overview: Power BI data sources
  • Connect to a SaaS solution
  • Upload a local CSV file
  • Connect to Excel data that can be refreshed
  • Connect to a sample
  • Create a Report with Visualizations
  • Explore the Power BI portal

Viz and Tiles

  • Overview: Visualizations
  • Using visualizations
  • Create a new report
  • Create and arrange visualizations
  • Format a visualization
  • Create chart visualizations
  • Use text, map, and gauge visualizations and save a report
  • Use a slicer to filter visualizations
  • Sort, copy, and paste visualizations
  • Download and use a custom visual from the gallery

Reports and Dashboards

  • Modify and Print a Report
  • Rename and delete report pages
  • Add a filter to a page or report
  • Set visualization interactions
  • Print a report page
  • Send a report to PowerPoint
  • Create a Dashboard
  • Create and manage dashboards
  • Pin a report tile to a dashboard
  • Pin a live report page to a dashboard
  • Pin a tile from another dashboard
  • Pin an Excel element to a dashboard
  • Manage pinned elements in Excel
  • Add a tile to a dashboard
  • Build a dashboard with Quick Insights
  • Set a Featured (default) dashboard
  • Ask Questions about Your Data
  • Ask a question with Power BI Q&A
  • Tweak your dataset for Q&A
  • Enable Cortana for Power BI

Publishing Workbooks and Workspace

  • Share Data with Colleagues and Others
  • Publish a report to the web
  • Manage published reports
  • Share a dashboard
  • Create an app workspace and add users
  • Use an app workspace
  • Publish an app
  • Create a QR code to share a tile
  • Embed a report in SharePoint Online

Other Power BI Components and Table Relationship

  • Use Power BI Mobile Apps
  • Get Power BI for mobile
  • View reports and dashboards in the iPad app
  • Use workspaces in the mobile app
  • Sharing from Power BI Mobile
  • Use Power BI Desktop
  • Install and launch Power BI Desktop
  • Get data
  • Reduce data
  • Transform data
  • Relate tables
  • Get Power BI Desktop data with the Power BI service
  • Export a report from Power BI service to Desktop

DAX functions

  • New Dax functions
  • Date and time functions
  • Time intelligence functions
  • Filter functions
  • Information functions
  • Logical functions
  • Math & trig functions
  • Parent and child functions
  • Text functions

Python Basics

  • The print statement
  • Comments
  • Python Data Structures & Data Types
  • String Operations in Python
  • Simple Input & Output
  • Simple Output Formatting
  • Deep copy
  • Shallow copy
  • Operators in python

Frequently Asked Questions (FAQ)

1: What is data analytics?

Ans:Data analytics is the process of inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making.

2:Why is data analytics important?

Ans: Data analytics helps organizations gain insights, make informed decisions, identify patterns and trends, optimize processes, and ultimately improve business performance.

3: What are the key components of data analytics?

Ans:The key components include data collection, data processing, data storage, analysis, and interpretation. Techniques like statistical analysis, machine learning, and data visualization are often employed.

4: What is the difference between descriptive, predictive, and prescriptive analytics?

Ans: Descriptive analytics focuses on summarizing historical data, predictive analytics involves forecasting future trends, and prescriptive analytics recommends actions based on the analysis of available data.

5: How is big data related to data analytics?

Ans:Big data refers to the large volume, velocity, and variety of data, while data analytics deals with extracting meaningful insights from data. Big data analytics involves specialized techniques to handle and analyze massive datasets.

6:What role does machine learning play in data analytics?

Ans: Machine learning is a subset of data analytics that involves the use of algorithms and statistical models to enable systems to improve their performance on a task over time without being explicitly programmed.

7: How is data analytics used in business?

Ans: Businesses use data analytics to understand customer behavior, optimize marketing strategies, improve operational efficiency, identify opportunities for growth, and mitigate risks.

8:What are some common challenges in data analytics?

Ans: Challenges include data quality issues, privacy concerns, the need for skilled professionals, choosing appropriate analytical techniques, and staying current with rapidly evolving technologies.

9:How is data visualization important in data analytics?

Ans:Data visualization is crucial for communicating insights effectively. It helps in making complex data more understandable and enables decision-makers to grasp patterns and trends quickly.

10:What ethical considerations are associated with data analytics?

Ans: Ethical considerations include issues related to privacy, consent, bias in algorithms, and the responsible use of data. Ensuring fairness and transparency in analytics processes is essential.

Why should you learn Data Analytics?


Learning data analytics is highly valuable in today's data-driven world for several compelling reasons. First and foremost, data analysts play a crucial role in extracting meaningful insights from vast and complex datasets, empowering organizations to make informed decisions. As businesses increasingly rely on data to drive strategies, understanding data analytics allows individuals to contribute to optimizing processes, identifying trends, and solving real-world problems. Moreover, data analysts are in high demand across various industries, offering excellent career prospects. By acquiring data analytics skills, one gains proficiency in tools and techniques for data manipulation, statistical analysis, and visualization, enhancing both problem-solving abilities and critical thinking. Overall, learning data analytics not only opens doors to diverse career opportunities but also equips individuals with the skills needed to navigate and succeed in the data-centric landscape of the modern workplace.
Jobs for Data Analysts


Data analysts are in high demand across industries due to the growing reliance on data-driven decision-making. In the business sector, data analysts are crucial for interpreting market trends, customer behavior, and operational efficiency. In finance, they contribute to risk assessment and portfolio management. Healthcare utilizes data analysts for optimizing patient care and resource allocation. Governments and non-profits benefit from data analysts in policy formulation and program evaluation. E-commerce companies rely on data analysts for personalized marketing strategies and inventory management. Tech firms use data analysts for product development and user experience enhancement. Media and entertainment industries leverage data analytics for audience engagement and content optimization. The versatility of data analytics transcends sectors, making it a key role in the contemporary job market with opportunities in diverse fields.
Training and Placement


Data analyst training and placement programs provide individuals with the essential skills and knowledge needed to excel in the field of data analytics. These programs typically cover a range of topics, including data manipulation, statistical analysis, programming languages like Python and R, and data visualization techniques. Hands-on, practical experience with real-world datasets is often a core component of the training. Many training programs also focus on industry-relevant tools and technologies such as SQL, Excel, and data visualization tools like Tableau or Power BI. Beyond technical skills, these programs may emphasize critical thinking, problem-solving, and effective communication of analytical findings. Successful completion of a data analyst training program enhances one's employability and opens doors to various industries, including finance, healthcare, marketing, and technology. Many training programs also offer placement assistance, connecting graduates with job opportunities and providing a pathway to launch a successful career as a data analyst.