Training on Data Science

About This Training:

This training is specially designed on demand of various IT companies who gives opportunity to college students for Internship.

Why Data Science Training:

As per previous experience from many companies they found that many students want to join Internship but they didn’t have enough knowledge to work on live projects of company or they lack in some particular fields. This Training is a bridge of knowledge between companies and students, so that companies get more skilled and qualified students for internship. In this training we are not only cover particular technology but we also covers from installation of software that needed

Get Certified with Our Training Program
What You Get:
Certificate:
  • Receive a signed certificate with the institution’s logo to verify your achievement and increase your job prospects.
  • Easily Shareable certificate
  • Add the certificate to your CV or resume, or post it directly on LinkedIn
Trainings:
  • Get access of 50 lessons training on Data Science
  • Assignments on Data Science
Placement Assistance:
  • Placement assistance to all students who successfully completed all modules.
  • Get updates on various companies vacancies, opportunities, placement drives.
Course Fee : ₹ 10000
Syllabus
Data Science
  • How to install python on windows 7/8.1/10
  • How to install Anaconda in windows 7/8.1/10
  • How to Launch Jupyter Notebook Using Anaconda
  • How To Import Libraries and Dataset for Linear Regression
  • Distribution Plot For Linear Regression
  • How To Find Outlier in Linear Regression
  • Linear Regression Pairplot
  • How To Use Label Encoder and Heatmap
  • How To Use Train Test and Split For Linear Regression
  • Linear Regression Model Creation and Model Training
  • Linear Regression Model Evaluation
  • How To Import libraries and dataset for Logistic Regression
  • Imputing Null Values
  • Plotting For Logistic Regression
  • How To Do The Pre-Processing For Logistic Regression
  • How To Use Train, Test and Split For Logistic Regression
  • How To Create Logistic Model and Model Evaluation
  • How To Import Libraries and Dataset
  • EDA (Exploratory Data Analysis) and Count Plot
  • How To Do The Pre-Processing
  • How To Use Train, Test and Split
  • How to Create Logistic Model and Logistic Model Evaluation
  • Decision Tree Entropy Model
  • Decision Tree Gini Model
  • Random Forest Model

 

  • How To Import Libraries and Dataset
  • Distribution Plot and EDA for Naive Bayes
  • How To Use Train, Test, Split and Logistic Model
  • Naive Bayes Model
  • How To Import Libraries and Dataset
  • Plotting and EDA For K-Means Cluster
  • Finding K and Elbow method for K-means Cluster
  • How Get Cluster Centers and Plotting
  • How To Import Libraries and Dataset
  • Distribution Plot and EDA For KNN
  • How To Use Train, Test and Split
  • How To Create KNN Model and Model Evaluation
  • How To Find K Optimum for KNN
  • How To Import Libraries, Dataset and Pre-Processing
  • Distribution Plot and EDA For SVM
  • How To Use Train, Test and Split the dataset
  • How to Create Logistic Model and Logistic Model Evaluation
  • Creating a Support Vector Machine and Model Evaluation