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Data Science Masterclass

( 3 Rating )

Instructor

pantech

Data Science Masterclass

Lifetime access

All levels

124 lessons

0 quizzes

510 students

Course Overview
Lessons
Instructor
Reviews

Data Science Masterclass

Data Science is a method of huge data analysis that automates analytical model building. It is a branch of artificial intelligence. A lot of opportunities are out there in the field of ml and AI in India. People already using ml in the field of image processing, pattern analysis, marketing, data analysis have a pretty good future in India. The Machine Learning sessions provide the participants technical training on the concepts and Machine Learning algorithms to develop the code. Participants will also learn to use different Python libraries. Instruction cum aided with live projects which will allow students to grasp concepts of the complete data science development life-cycle.

Learning Path

The learning path of any learning concept is rather very important, as it is the way through which the learning process is enabled. This data Science Master class is designed to make the participant learn from scratch and master the concepts with ease.

Python for Data Science and advance Programming
Libraries – Pandas, Numpy, Matplotlib, Seaborn, and Sklearn
Python – Data Aggregation, Tokenization, Visualization, Statistical Analysis.
Tools – Tableau and Power -Bi.
Industry Projects – House Price Prediction, Customer Segmentation, Spam Classification, and More.

Program Overview

Day -1: Python for Data
Science (5 Solved end-to-end Data Science Projects in Python)

Day -2: Advanced Python Programming

Day -3: Pandas Library – Introduction

Day -4: Pandas Library – Data Structures

Day -5: Numpy library – Array Operations | Mathematical Functions

Day -6: Numpy – Sort, Search, and Counting Functions

Day -7: Matplotlib, Histogram Using Matplotlib | I/O With Numpy

Day -8: Matplotlib Library – Introduction, Pyplot API | Types Of Plots

Day -9: Seaborn Library

Day -10: SKLearn Library

Day -11: Google Colab Notebook

Day -12: Python – Date and Time, Data Wrangling

Day -13: Python – Data Aggregation

Day -14: Python – Word Tokenization, Stemming, and Lemmatization

Day -15: Python – Data Visualization

Day -16: Python – Statistical Analysis

Day -17: Python – Types Of Distribution

Day -18: Python – Correlation, Chi-Square Test , Linear Regression

Day -19: Tableau – Introduction and Tools

Day -20: Tableau – Data Sources , Worksheets

Day -21: Spatial Data Science For Covid-19 Disease Prediction

Day -22: Power-BI – Introduction, Installation Steps, and Architecture

Day -23: Power-BI – Data Modelling, Visualization Options | Excel Integration

Day -24: Parkinson’s Disease Prediction – XG Boost Classifier

Day -25: House Price Prediction using Random Forest Regression

Day -26: Customer Segmentation Using ML – K-Means Clustering

Day -27: Home Loan Prediction using Decision Tree Classifier

Day -28: Spam Classification using NLP

Day -29: Hand-Written Digit Recognition Using CNN

Day -30: Churn Prediction using Deep Learning

Orientation - Data Science Master Class
- Orientation – Data Science Master Class
- Downloadable – Orientation – Data Science Master Class
Day -1: Python for Data Science (5 Solved end-to-end Data Science Projects in Python)
- Python – Introduction
  10 minutes
- Python – Applications Of Python
  11 minutes
- Python – Anaconda Navigator Download
  11 minutes
- Python – Variable Types
  11 minutes
- Downloadable – Python for Data Science
Day -2: Advanced Python Programming
- Python – Tuples
  11 minutes
- Tuples and Dictionaries
  11 minutes
- Classes and Objects
  12 minutes
- Class and Inheritance
  10 minutes
- Downloadable – Advanced Python Programming
Day -3: Pandas Library – Introduction
- Pandas – Introduction
  11 minutes
- Pandas – Series Input
  10 minutes
- Pandas – Data Structures
  10 minutes
- Pandas – Dictionary
  3 minutes
- Downloadable – Pandas Library – Introduction
Day -4: Pandas Library – Data Structures
- Pandas – Access Series Elements
  11 minutes
- Pandas – Data Frames
  11 minutes
- Pandas – Data Frames 2
  12 minutes
- Pandas – Data frames 3
  12 minutes
- Downloadable – Pandas Library – Data Structures
Day -5: Numpy library – Array Operations | Mathematical Functions
- Downloadable Numpy library – Array Operations | Mathematical Functions
- Numpy- Introduction
  11 minutes
- Numpy – Arrays
  11 minutes
- Numpy- D-type, shape Attribute
  11 minutes
Day -6: Numpy – Sort, Search, and Counting Functions
- Numpy – Slicing
  11 minutes
- Numpy – Indexing , Slicing
  13 minutes
- Numpy – around, floor function
  20 minutes
- Downloadable – Numpy – Sort, Search, and Counting Functions
Day -7: Matplotlib, Histogram Using Matplotlib | I/O With Numpy
- Matplotlib – Introduction
  10 minutes
- Numpy – Simple PLot
  11 minutes
- Matplotlib-pylab
  19 minutes
- Downloadable – Matplotlib, Histogram Using Matplotlib | I/O With Numpy
Day -8: Matplotlib Library – Introduction, Pyplot API | Types Of Plots
- Matplotlib – FigureWindow
  15 minutes
- Matplotlib – Adv, Sales(TV and Smartphones)
  10 minutes
- Matplotlib – Subplot
  22 minutes
- Downloadable -Matplotlib Library – Introduction, Pyplot API | Types Of Plots
Day -9: Seaborn Library
- Seaborne – Introduction
  11 minutes
- Seaborne – Jointplot
  16 minutes
- Seaborne – Pairplot, Jointplot
  13 minutes
- Downloadable – Seaborn Library
Day -10: SKLearn Library
- Scikit-Learn Introduction
  14 minutes
- Scikit Learn Example
  15 minutes
- Scikit Learn Train Test Split Module
  26 minutes
- Downloadable – SKLearn Library
Day -11: Google Colab Notebook
- Google Colab – Introduction
  14 minutes
- Google Colab – Options
  11 minutes
- Google Colab – Graphical Outputs
  21 minutes
- Downloadable – Google Colab Notebook
Day -12: Python – Date and Time, Data Wrangling
- Downloadable – Python – Date and Time, Data Wrangling
- Data and Time Introduction
  11 minutes
- Date and Time – Example
  10 minutes
- Date and Time – Arithmetic
  21 minutes
Day -13: Python – Data Aggregation
- Downloadable – Python – Data Aggregation
  15 minutes
- Data Wrangling – Introduction
  15 minutes
- Data Science – Merging, Grouping
  11 minutes
- Data Science – Concat, Reading HTML Page
  11 minutes
Day -14: Python – Word Tokenization, Stemming, and Lemmatization
- Word Tokenization – Introduction
  6 minutes
- Sentence Tokenization – Ex 2
  6 minutes
- Stemming and Lemmatization
  20 minutes
- Downloadable – Python – Word Tokenization, Stemming, and Lemmatization
Day -15: Python – Data Visualization
- Data Visualization – Introduction
  12 minutes
- Data Visualization – Simple plot 2
  12 minutes
- Downloadable – Python – Data Visualization
Day -16: Python – Statistical Analysis
- Statistical Analysis
  10 minutes
- Mean median and mode
  12 minutes
- Statistical Analysis 2
  12 minutes
- Downloadable – Python – Statistical Analysis
Day -17: Python – Types Of Distribution
- Types Of Distribution
  10 minutes
- Types Of Distribution 2
  11 minutes
- Poisson Distribution
  10 minutes
- Downloadable -Python – Types Of Distribution
Day -18: Python – Correlation, Chi-Square Test , Linear Regression
- Types Of Distribution, Correlation
  10 minutes
- Correlation, Chi-Square Test
  10 minutes
- Correlation
  15 minutes
- Downloadable – Python – Correlation, Chi-Square Test , Linear Regression
Day -19: Tableau – Introduction and Tools
- Introduction to Tableau
  10 minutes
- Installation – Steps
  12 minutes
- Tableau – Visual Analysis
  12 minutes
- Downloadable -Tableau – Introduction and Tools
Day -20: Tableau – Data Sources , Worksheets
- Tableau – Different Options
  12 minutes
- Tableau – Analysing Different Data Sources
  11 minutes
- Tableau – Combining Fields , Dashboard Option
  16 minutes
- Download – Data Sources , Worksheets
Day -21: Spatial Data Science For Covid-19 Disease Prediction
- Spatial Data Science – Introduction
  11 minutes
- COVID19 Disease Prediction
  13 minutes
- COVID19 Disease Prediction – IMPL
  21 minutes
- Downloadable – Spatial Data Science For Covid-19 Disease Prediction
Day -22: Power-BI – Introduction, Installation Steps, and Architecture
- Power BI – Introduction
  11 minutes
- PowerBI – Architecture
  12 minutes
- PowerBI – Data Source
  18 minutes
- Downloadable – Power-BI – Introduction, Installation Steps, and Architecture
Day -23: Power-BI – Data Modelling, Visualization Options | Excel Integration
- PowerBI – DAX
  11 minutes
- Data Visualization
  11 minutes
- Downloadable – Data Modelling, Visualization Options | Excel Integration
Day -24: Parkinson’s Disease Prediction – XG Boost Classifier
- Ensemble Learning
  11 minutes
- Ensemble Techniques
  11 minutes
- Parkinson’s Disease IMPL
  18 minutes
- Downloadable – Parkinson’s Disease Prediction – XG Boost Classifier
Day -25: House Price Prediction using Random Forest Regression
- Random Forest Regression
  10 minutes
- House Price Prediction
  12 minutes
- House PDN IMPL
  20 minutes
- Downloadable – House Price Prediction using Random Forest Regression
Day -26: Customer Segmentation Using ML – K-Means Clustering
- K-Means Clustering – Introduction
  12 minutes
- K-Means Algorithm , Working, Segmentation
  16 minutes
- Customer Segmentation Impl
  13 minutes
- Downloadable – Customer Segmentation Using ML – K-Means Clustering
Day -27: Home Loan Prediction using Decision Tree Classifier
- Decision Tree Algorithm
  12 minutes
- Home Loan Prediction
  10 minutes
- Home Loan Pdn Impl
  20 minutes
- Downloadable – Home Loan Prediction using Decision Tree Classifier
Day -28: Spam Classification using NLP
- NLP- Introduction
  11 minutes
- NLP Techniques
  7 minutes
- Spam Classification Impl
  17 minutes
- Downloadable – Spam Classification using NLP
Day -29: Hand-Written Digit Recognition Using CNN
- ANN – Introduction
  10 minutes
- ANN – Types Of ANN
  11 minutes
- CNN – Implementation
  20 minutes
- Downloadable – Hand-Written Digit Recognition Using CNN
Day -30: Churn Prediction using Deep Learning
- ANN – Introduction
  12 minutes
- Deep Learning – Concepts
  16 minutes
- Churn Prediction – Implementation
  5 minutes
- Downloadable – Churn Prediction using Deep Learning

pantech

5.0

3 total

Reviews

narsalepratik881@gmail.com

Good teaching

THANKS MADAM FOR NICE TEACHING AND LEARNING PROCESS
Richard William

Data science

Machine
Vamshi krishna Puttappagari

First comment

Really good flatform for Data science

9 Comments

Marut Dev Sharma says:

January 21, 2022 at 7:30 pm

THANKS MADAM FOR NICE TEACHING AND LEARNING PROCESS

IF I HAVE A PERSONAL DOUBT HOW CAN I CONTACT YOU MADAM
AS IN CHATBOX IT IS VERY FAST MOVING

Reply
Nimsakhare Vedika Vilas says:

January 23, 2022 at 1:54 pm

Ok

Reply
Vamshi krishna Puttappagari says:

January 23, 2022 at 11:21 pm

First comment

Reply
Yemba Uzilo is says:

January 24, 2022 at 4:41 pm

Very much informative this course would like to 5ake place to this live session

Reply
Brij Bhushan says:

February 1, 2022 at 8:10 pm

Your blog helped me to improve myself in many ways thanks for sharing this kind of wonderful informative blogs in live. I have bookmarked more article from this website. Such a nice blog you are providing !

Reply
MALAKONDAIAH KUMMITHA says:

February 22, 2022 at 1:02 pm

Good platform to learn the course.

Reply
Jagadeesh babu Inaganti says:

February 22, 2022 at 1:09 pm

Thanks madam for nice teaching
And thanks to pantech e learning

Reply
Konidena Parvathi says:

February 22, 2022 at 8:01 pm

THANKS MADAM FOR NICE TEACHING AND LEARNING PROCESS

Reply
Ratna Sandeep Arnipalli says:

February 24, 2022 at 2:38 pm

Thank you for the great sessions.

Reply