ICT-108 – Data Science Certification Course

Introduction to Data Science

  • Defining Data Science
  • What Does a Data Science Professional Do?
  • Data Science in Business
  • Data Science People
  • The fundamentals of descriptive statistics
  • Measures of central tendency, asymmetry, and variability
  • Distributions
  • Estimators and estimates
  • Inferential statistics
  • Hypothesis testing
  • Regression Analysis
  • Dealing with categorical data

R Programming

  • Introduction to R basics
  • Data structures in R
  • Basics of R Programming
  • Working with Data in R
  • Stings and Dates in R
  • Introduction to Business Analytics
  • Data Structures
  • Data Visualization
  • Statistics for Data Science
  • Classification
  • Clustering
  • Association

Data Science with Python

  • Python Basics
  • Python Data Structures
  • Python Programming Fundamentals
  • Working with NumPy arrays
  • Data Science Overview
  • Data Analytics Overview
  • Statistical Analysis and Business Applications
  • Python Environment Setup and Essentials
  • Mathematical Computing with Python (NumPy)
  • Scientific computing with Python (Scipy)
  • Data Manipulation with Pandas
  • Machine Learning with Scikit–Learn
  • Natural Language Processing with Scikit Learn
  • Data Visualization in Python using matplotlib
  • Web Scraping with BeautifulSoup

Machine Learning

  • Introduction to Artificial Intelligence and Machine Learning
  • Data Wrangling and Manipulation
  • Supervised Learning
  • Feature Engineering
  • Supervised Learning-Classification
  • Unsupervised learning
  • Time Series Modelling
  • Ensemble Learning
  • Recommender Systems
  • Text Mining

Tableau

  • Getting Started with Tableau
  • Working with Tableau
  • Deep diving with Data and Connections
  • Creating Charts
  • Adding calculations to your workbook
  • Mapping data in Tableau
  • Dashboards and Stories
  • Visualizations for An Audience

Big Data Hadoop and Spark Developer

  • Introduction to Big Data and Hadoop Ecosystem
  • HDFS and Hadoop Architecture
  • Map Reduce and Sqoop
  • Basics of Impala and Hive
  • Working with Hive and Impala
  • Type of Data Formats
  • Advanced HIVE concept and Data File Partitioning
  • Apache Flume and HBase
  • Apache Pig
  • Basics of Apache Spark
  • RDDs in Spark
  • Implementation of Spark Applications
  • Spark Parallel Processing
  • Spark RDD Optimization Techniques
  • Spark Algorithm
  • Spark SQL

Data Science Project Work

  • Data Processing
  • Model Building
  • Model Fine-tuning
  • Dashboarding and Representing Results

Want to get admission in our institute? Go Ahead!

Call: +91 62849 16580; 9876613092