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Course
Duration

80

hours

Advantages of Data Science Course

35,000

Average Salary per Annum in UK

3,00,000

Job Vacancies across the world

hiring partners

We are globally connected with the top IT companies

We are connected with companies with different industries across the nation. Our dedicated placement cell is
constantly striving to get more companies on-board

About Data Science Training & Certification

Pre-Requisites

  • Basic Python (Intermediate Level)
  • Git
  • Basic Linux

Mathematics for Data Science

  • Statistics – Descriptive & Inferential Stats
  • Probability – Basic & Conditional Probability, Bays Theorem
  • Algebra Mathematics – Linear & Polynomial Equations
  • Matrices & Vectors – properties, operations, use cases
  • Calculus

Data Collection Tools & Techniques

  • Web Scrapping
  • Logging
  • DBMS Queries
  • Data Using APIs

Data Engineering or Data Preprocessing

  • Data Formats & Structures (csv, tsv, excel sheet etc.)
  • Assessing Data for Quality Cheque
  • Data Wrangling Techniques
    • Discovering
    • Structuring
    • Cleaning
    • Enriching
    • Validating
    • Publishing
  • Data Transformations
    • One Hot Encoding
    • Label Encoding
    • Normalization of Data

Data Analysis or Getting Insights from Data

  • Process of Question Building
  • Answering Common Questions related to data
  • Application of Stats to find useful information out of data
  • Data Modeling
  • Hypothesis Testing
  • Predictive Analysis
  • Text Analysis

Data Visualization

  • Aesthetics of Plots
  • Creating Charts, Plots and Maps
  • Bar Chart, Box Plot, Histograms, Line Plot
  • Scatter Plot, Violin plots, Word Cloud, Maps etc.
  • Exploratory Data Analysis
  • Understanding Trends, Outliers, and Pattern in Data
  • Creating Live Plots

Machine learning

  • History, Scope and Future of Machine Learning
  • Supervise Machine Learning Techniques
    • Regression Algorithms
      • SLR, Multiple Linear Regression, Multivariant Linear Regression
      • Polynomial Regression
      • Lasso & Ridge Regression
      • Gradient Descent
    • Classification Algorithms
      • Logistic Regression
      • Decision Trees Classifiers
      • Random Forest Classifiers
      • Naïve Bays Classifiers
      • K-Nearest Neighbors (KNN)
      • Support Vector Machines (SVM)
  • Unsupervised Machine learning Techniques
    • Clustering
      • K-means Clustering Algorithm
      • DBSCAN Clustering Algorithm
    • Dimensionality Reduction
      • Linear Discriminant Analysis
      • Principle Component Analysis
  • Text Processing
    • Bag of Words, TF, IDF
    • Sentiment Analysis
    • Word Clouds
  • Evaluation Matrices
    • Mean Square, Mean Absolute, RSS and TSS errors
    • R2 Score for Regression Accuracy
    • ROC and AUC Curves for Performance Measuring
    • Classification Report & Confusion Matrix
    • Precision & Recall Matrix
    • Accuracy Score for Classification Accuracy
  • Optimization Techniques
    • Hyper Parameter Tuning
    • Grid Search
    • Cross Validation
    • Early Stopping
  • Introduction to Deep Learning
    • Neural Networks

Pyspark

  • Big Data
  • Distributed computing
  • Distributed Storage
  • Data Analysis on Bigdata using Pyspark
  • Machine Learning on Bigdata using Pyspark

Case Studies

  • Various Case Studies Related to Data Science & Machine Learning

Capstone Project

  • For Each Section and Algorithm, we will Create a Capstone Project which will show case your Detailed Knowledge

Python Modules Used in This Course

  • Exploratory Data Analysis
    • numpy, scipy, pandas, matplolib, seaborn, plotly, folium
  • Data Scrapping
    • Beautiful soup, Requests
  • Machine Learning
    • Sklearn, tensorflow, keras

Induction For Data Science

End to End Training on
Live Project after finishing module

Trainers Profile

Amit Mehta

More than 14+ year experience in Software Engineering with solid foundation. He also contribute as visitor lecturer in University. Providing Corporate Training to Organisation as well.


Oracle Java Certified + AWS DevOps professionals with M.Sc in Software Engineering from NIELIT in India.


Working as Lead Application Developer in Corporate sector.

Take a career boost & get your knowledge in shape with Programming