data science

Data Science institute in Greater Noida

Best Data Science training institute in greater noida.

At INCAPP, We do not only teach concepts, We make sure you able to understand and implement practicaly.

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Course Curriculum

Data Science using Python is a very popular course. It allows Python Programmers to extract deep knowledge from huge amounts of data. It provides the necessary skills to analyze and visualize the complex data.

  • What is Data Science?
  • Why Data Science?
  • Applications of Data Science
  • Scope of Data Science
  • Introduction to Libraries for Data Science
  • Tools required for Data Science

  • Introduction to MY-SQL
  • Installing MYSQL
  • DML, DDL, & DQL Commands
  • Constraints:
    • NOT NULL, NULL, UNIQUE
    • Introduction to Keys in SQL
      • Primary Key
      • Unique Key
      • Foreign Key
      • Composite Key
      • Candidate Key
    • CHECK ,DEFAULT
  • SQL Commands
    • DDL (Data Definition Language)
      • CREATE
        • CREATE DATABASE
        • CREATE TABLE
        • CREATE INDEX
        • CREATE VIEW
        • CREATE SCHEMA
      • ALTER
        • ALTER TABLE
        • ALTER INDEX
      • DROP
        • DROP TABLE
        • DROP DATABASE
        • DROP INDEX
        • DROP VIEW
        • DROP SCHEMA
      • TRUNCATE
        • TRUNCATE TABLE
    • DQL (Data Query Language)
      • SELECT
        • SELECT *
        • SELECT column1, column2, ...
        • SELECT DISTINCT
        • SELECT ... FROM ... WHERE ...
        • SELECT ... FROM ... ORDER BY ...
        • SELECT ... FROM ... GROUP BY ...
        • SELECT ... FROM ... HAVING ...
        • SELECT ... FROM ... JOIN ...
      • FETCH
        • FETCH NEXT
    • DML (Data Manipulation Language)
      • INSERT
        • INSERT INTO
      • UPDATE
        • UPDATE ... SET ...
      • DELETE
        • DELETE FROM ... WHERE ...
      • LIKE Operator
        • WHERE column_name LIKE pattern
      • JOINs
        • INNER JOIN
        • LEFT JOIN
        • RIGHT JOIN
        • FULL JOIN
        • CROSS JOIN
        • SELF JOIN
      • MySQL Functions
        • Aggregate Functions
          • COUNT()
          • SUM()
          • AVG()
          • MIN()
          • MAX()
        • String Functions
          • CONCAT()
          • SUBSTRING()
          • LENGTH()
          • UPPER()
          • LOWER()
        • Date and Time Functions
          • NOW()
          • DATE()
          • TIME()
          • YEAR()
          • MONTH()
          • DAY()
          • HOUR()
          • MINUTE()
          • SECOND()

  • What is Statistics?
  • Why Statistics?
  • Mean, Median and Mode
  • Standard Deviation and Variance
  • Normal Distribution

  • Understanding Jupyter Notebook
  • Downloading and Installing the Anaconda
  • Creating Document in Jupyter Notebook
  • Writing and Executing Python in Jupyter Notebook
  • Using the Code Mode of Jupyter Notebook
  • Using the Markdown Mode of Jupyter Notebook
  • Using the Heading Mode of Jupyter Notebook

  • Introduction to Numpy
  • Creating One-dimensional Numpy Arrays
  • Indexing and Slicing in One-dimensional Numpy Array
  • Operations on One-dimensional Numpy Array
  • Creating Multi-dimensional Numpy Arrays
  • Indexing and Slicing in Multi-dimensional Numpy Array
  • Operations on Multi-dimensional Numpy Array
  • Difference between Numpy Array and List
  • Finding time complexity of Numpy Array and List
  • Finding space complexity of Numpy Array and List

  • Introduction to Pandas
  • Understanding Series and DataFrame
  • Series
    • Creating Series from List
    • Creating Series from Dictionary
    • Indexing and Slicing in Series
  • DataFrame
    • Creating DataFrame from List
    • Creating DataFrame from Dictionary
    • Creating DataFrame from Series
    • Indexing and Slicing in DataFrame
    • Looping through DataFrame
    • Removing Rows and Columns from DataFrame
    • Sorting Data in DataFrame
    • Finding Missing values in DataFrame
    • Removing Missing values in DataFrame
    • Data Manipulation in DataFrame
      • Exploratory Data Analysis in DataFrame
      • Merging DataFrame
      • Data Encoding in DataFrame
      • Working with Dates and Times Data in DataFrame
      • Working with Real-time data using Pandas
  • Data Cleaning in DataFrame
    • Replacing Missing values in DataFrame
    • Data Encoding in DataFrame
    • One Hot Encoding in DataFrame
  • Data Import and Export
    • Reading Data from CSV files
    • Writing Data to CSV files
    • Reading Data from Excel files
    • Writing Data to Excel files
    • Reading Data from SQL databases
    • Writing Data to SQL databases
    • Reading Data from JSON files
    • Writing Data to JSON files
    • Reading Data from HTML files
    • Writing Data to HTML files
  • Advanced Operations
    • Integration with NumPy
    • Integration with matplotlib for visualization
    • Integration with seaborn for advanced visualization

  • Introduction to Matplotlib
  • Understanding Matplotlib's Architecture
  • Basic Plotting
    • Line Plot
    • Scatter Plot
    • Bar Plot
    • Histogram
    • Pie Chart
  • Customizing Plots
    • Adding Titles and Labels
    • Changing Colors and Styles
    • Adding Legends
    • Setting Axis Limits
    • Adding Gridlines
    • Annotating Plots
  • Subplots
    • Creating Subplots
    • Customizing Subplots
    • Sharing Axis Limits
  • Advanced Plotting
    • 3D Plotting
    • Polar Plot
    • Contour Plot
    • Heatmap
    • Box Plot
  • Saving and Exporting Plots
    • Saving Plots as Image Files
    • Exporting Plots to PDF
  • Integration with Pandas
    • Plotting Pandas DataFrames
    • Customizing Pandas Plots
  • Interactive Plotting
    • Adding Interactivity with Widgets
  • Working with Multiple Figures
    • Managing Multiple Figures
    • Saving Multiple Figures

  • Introduction to Seaborn Libraryn
  • Styling Functionsn
  • Color Palletsn
  • Distributed Plotsn
  • Categorical Plotsn

  • Introduction to SciPy
  • Creating Functions
  • Models of SciPy

  • Introduction to Power BI
    • What is Power BI?
    • Why use Power BI?
  • Power BI Components Overview
    • Power BI Desktop
    • Power BI Service
    • Power BI Mobile
  • Getting Started with Power BI Desktop
    • Downloading and Installing Power BI Desktop
    • Interface Overview
    • Loading Data
    • Building Visualizations
  • Power BI Basics
    • Data Sources
      • Excel
      • Databases (SQL Server, MySQL, etc.)
      • Web Data Sources
    • Data Transformation
      • Cleaning and Shaping Data
      • Data Modeling
    • Creating Basic Visualizations
      • Bar Charts
      • Line Charts
      • Pie Charts
      • Tables
    • Introduction to DAX (Data Analysis Expressions)
      • Calculated Columns
      • Measures
      • DAX Functions
  • Advanced Power BI Techniques
    • Advanced Data Modeling
      • Relationships
      • Hierarchies
      • Calculated Tables
    • Advanced Visualizations
      • Drilldown Charts
      • Treemaps
      • Waterfall Charts
      • Custom Visuals
    • Power BI Integration
      • Integrating with Excel
      • Integrating with Azure Services
      • Integrating with SharePoint
      • Using Power BI REST APIs

  • Introduction to OpenCV
  • Reading Images
  • Understanding Gray Scale Image
  • Resizing Images
  • Face and Eyes Classification
  • How to Use Webcam in OpenCV
  • Building Image DataSet
  • Capturing Video
  • Face Classification in Video

  • Project Work

How We Help You To Learn Coding

INCAPP is a leading coding institute committed to providing high-quality training programs to students, professionals, and organizations. We aim to empower individuals with the coding skills to achieve personal and professional growth and help organizations enhance the productivity and effectiveness of their workforce.

1
Expert Instructors

Top-class instructors, experts in their fields, teach through practical training.

2
Assignments

Understand all concepts through well-structured assignments.

3
Doubt Resolution

Dedicated assistance provided to clarify doubts, featuring two types of instructors: Class Instructor and Lab Instructor.

4
Projects

Gain a comprehensive understanding of the technology through project work, guided by your instructor.

WHY INCAPP ?


Outstanding students deserve the finest learning environment. At INCAPP, we guarantee a superior learning experience and personalized support to ensure your success.

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Top-Notch Classroom with Expert Instructor

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Comprehensive Study Materials

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Continuous Feedback and Monitoring

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Guaranteed Course Completion

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Project-Based Learning

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Course Completion Certification

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Dedicated Support for Doubt Resolution

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Placement Assistance

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Individual Attention to Each Student

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In-Class Assignment Sessions

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