> Data Science Introduction.
> Data Science Modules.
> Application of Data Science across multiple Industries.
> Career Opportunities in Data Science
> Scope of Data Science across different Business Domains
> How Data Science used in ERP and CRM?
> How Data Science used in HR and Operational Management?
> How Data Science Used in Supply Chain Management?
> How Data Science Used in Logistics?
> Data Collection Methods and Data Cleaning
> Data Processing Process
> EDA – Exploratory Data Analysis
> Machine Learning and Data Visualisation
> Building the automated Model
> Python Introduction
> Python IDE – Spyder, Jupiter and Notebook
> Numpy Packages
> Pandas Packages
> Matplotlib Packages
> Scipy Packages
> Sklearn Packages
> Variable Declaration
> String Declaration
> Tuple Declaration
> Python Programming
> Dictionary Declaration
> List Declaration
> Set Declaration
> Python Data Types
> Declaration of Array
> Universal Function of Numpy
> Binary Functions of Numpy
> Logical Functions of Numpy
> Statistical Functions of Numpy
> Pandas Packages
> Accessing File Processing
> Merging the Dataframe
> Joins – Inner,Outer,Left and Right
> handling the Null values
> Handling the Duplicates
> Introduction to matplolib packages
> Representation of Line Graph
> Representation of Multi Line Graph
> Including the Legends
> Representation of Histogram
> Representation of Scatter Diagram
> Representation of Box Plot
> Representation of Bar Graph
> Representation of Area Chart
> Representation of Dual Axis
> Array Shapping Using Numpy Package
> Reverse Matrix Analysis using Numpy Package
> Python Operators – Addition, Subtration and Multiplication
> Boolean Operators Execution
> String Manupulation
> Execution of IF Loop, IF-ELSE Loop
> Execution of For Loop
> Execution of While Loop
> Execution of IF-ELSE-ELSEIF Loop
> Handling Missing Values
> Handling Duplicates Values
> Handling Data Preparation Process
> Python – Funtions with Arguments
> Python – Funtions without Arguments
> Python – Functions with Arbitary Arguments
> Python – Functions with Keyword Arguments
> Python – Data Collection Methods
> Primary and Secondary Sources of Data
> File Processing using Python
> Linear Predictive Analysis
> Implementation of Predictive Analysis Using Python
> What is Multiple Predictive Model?
> Building the Multiple Predictive Model using Python
> Assumption of Multiple Predictive Model
> AutoCorrelation,MultiColliniearity and Hetrosadacity
> How Simple Predictive Model used in real time application
> How Multiple Predictive Model used in Real Time Application
> Simple Predictive Model used in Real Time Industry
> Multiple Predictive Model used in Real Time Industry
> Comparing Simple and Multiple Predictive Model using Python
> What is Correlation Analysis?
> Correlation Coefficient and Hypothesis Testing
> Product Movement Correlation, Partial Correlation and Non Metric Co-relation
> Introduction to Classification Model
> Framming Single and Multiple Predictor Model
> Application of Classification Model
> Introduction to Discriminant Analysis
> Two Group Discriminant Analysis
> Three Group Discriminant Analysis
> Multiple Group Discriminant Analysis
> Application of Discriminant Analysis
> Introduction to Association Rule
> What is Apriori Algorithm?
> How Apriori Algorithm used to Build to Recommendation System?
> What is MBA(Market Basket Analysis)?
> Application of MBA in Retail and Telecom Sectors
> How MBA helps to Build the Recommendation System
Image Processing and Image Extraction |
Image-Histogram and Contrast Measures |
Image Processing and Object Regognition |
Viola Jones Algorithm – Face Regognition |
Introduction to Time Series Analysis |
Trend Line Analysis, Pattern Identification |
Time Series Smothening Methods |
Time Series Prediction Analysis |
Differnece between AI and Machine Learning |
Differnece between Machine Learning and Deep Learning |
Differnece between Machine Learning and Data Science |
Differnece between Machine Learning and Deep Learning |
Data Architecture Design and Data Warehousing |
Schema Design – Star Schema, Snow Flake Schema and Fact Concelltation |
Master Data Management(MDM) |
You get lifetime access to our community and network of professionals that will expose you to some of the best opportunities for work and internships in India.
Professional support expert engineers are always available to address all your questions or concerns. Plus we have a close-knit community to help you through your journey.(Platinum Batch)
Learners will work on one project that gets designed by working professionals and is a replica of the problems they’re currently addressing working in the industry.
A basic level of interest and keen dedication is all that you need to complete this course and successfully become a sought-after Power BI professional.
Priyanshu Chaubey will be your Mentor and Trainer, working in Accenture, Ex – Tech Mahindra
Data Science is currently one of the highest-paying careers in India and the average salary is about 10 LPA according to Data on Glassdoor.
After Enrollment to the Master Data Science Bootcamp we provide an optional upgrade from the current (Gold) Membership to Platinum Membership where students receive the Additional Benefits.
Yes we provide placement Assistance at this course (which is in platinum ,membership).