Executive Diploma in Data Science

Hours   Total: 240 Hrs Instructor   Instructional: 140 Hrs Project   Project: 60 Hrs
Assignments   Assignments: 40 Hrs Hours   2 hrs/per day Language   English
Hours Total:
268 Hrs
Instructor Instructional:
140 Hrs
Project Project:
60 Hrs
Assignments Assignments:
60 Hrs
Employability Skills Employability Skills:
20 Hr
Hours 2 hrs/per day
Language English
Live

Live

Instructor Led Program

Case

Workshop

For hands-on learning

projects

Projects

From real world scenarios

Certification

Certification

Widely recognized by the industry

Course Overview

The business landscape today is filled with technological developments where we discover unlimited data on a daily basis around us. At this juncture, data science is detrimental to all data-driven decisions and business strategies across all spectrums. With a deficit in talent and the amount of data hitting off the charts at a variable pace, data science professionals are in high demand, and it has become the most sought-after skill today. While the number of jobs requiring data science skills today falls within 20%, it is estimated to reach over 27% by 2026, which makes it more relevant than ever.

Our course is specifically designed to provide credible assistance to freshmen in order to train them in the fundamentals of machine learning, programming, and statistical modeling. The all-new Executive Diploma course in Data Science will help you handle, manage, analyse and interpret data using tools such as Spark, Hadoop, NoSQL, and more. It will be an immersive learning experience with data, with engaging live sessions and interactions.

Program Fee   ₹79900
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    Schedule on demand

Learning Outcome

Upon completing the course, you are bound to gain control over the following areas:

  • Understanding the tools and techniques employed in Data science and machine learning
  • Learning to navigate the Hadoop ecosystem
  • Ingesting data using various tools
  • Implementing machine learning algorithms with an in-depth understanding of data structure and data analysis.
  • Performing data frame operations in Spark using SQL queries.

Syllabus

Module 01 Complete Introduction to Python Programming
  • Introduction to Python
  • Standard Library Functions
  • OOPS concepts
  • Graphical User Interface
  • Networking-Client and Server Program

Hands-On Assignments - 10 Hours

Module 02 Python for Data Science and Advanced Data Analytics
  • Understanding of Distribution theorems
  • Concept of Structured and Unstructured data
  • Clustering methods and Its implementations
  • TensorFlow, Keras Libraries for numerical computations
  • Python Libraries used in Data science and analytics process such as NumPy, Panda, SciKit many more.

Hands-On Assignments - 10 Hours

Module 03 Machine Learning Essentials
  • Introduction to Machine Learning
  • Introduction to R programming
  • Statistics Essentials
  • Knowledge extraction using Statistics Essentials
  • Pre program preparation
  • Classification algorithm, Decision Tree
  • Linear classifier: Naïve Bayes Classifier, Case study
  • Logistic regression, case study
  • Regression Analysis, case study
  • Survival Analysis, Case study
  • Introduction Clustering, Euclidean Distance
  • Hierarchical clustering, case study
  • k-means clustering, Case Study

Hands-On Assignments - 10 Hours

Module 04 Course on Artificial Intelligence
  • Introduction to Artificial Intelligence
  • Learning basic statistics and probability theory
  • Introduction to Python Programming, Tensor flow
  • Introduction to machine learning, Supervised algorithm for AI problem
  • Supervised algorithm for AI problem, Decision Tree
  • Introduction to OPEN-CV, Library and packages to use for image and video processing, Concept of image segmentation in AI
  • Introduction to NLP(nltk), Text mining using NLP
  • Text mining processes (tokenizer, stemming, lemmatization, pos, syntax, chunking etc)
  • Understanding various components of Neural Networks
  • Keras, Theano, Tensor Flow - Installation, Introduction to Keras, Theano, Tensor Flow.
  • K-means clustering, Case Study

Hands-On Assignments - 10 Hours

Module 05 Course on Hadoop and Spark
  • Fundamentals of Hadoop and the ecosystem around it
  • Working on HDFS, MapReduce, Hive, PIG, and more
  • Working alongside Avro Data formats
  • Understanding Spark, Spark SQL, Data frame and other Spark writing applications
  • Processing RDD in Apache Spark and real time data

Hands-On Assignments - 10 Hours

Module 06 Essentials of SQL
  • Introduction
  • Data Definition Language (DDL), Data Manipulation Language (DML), Data Control Language (DCL), Data Query Language (DQL) and Transaction Control Language (TCL)
  • Constraints
  • Other essential clauses, and operators
  • Working with Multiple tables

Hands-On Assignments - 10 Hours

Module 07 Advanced Data Visualization with Tableau
  • Visual Analytics
  • Data Visualization
  • Tableau Prep Builder tool
  • Tableau UI components
  • Geographic Visualizations in Tableau
  • Building Dashboards and Stories within Tableau

Hands-On Assignments - 10 Hours

Guided Projects

Creating one dimensional Numpy Array

10 Hrs

Creating two dimensional Numpy Array

10 Hrs

Project on joining and data extract using Tableau

10 Hrs

Performing data analysis on hospital domain in SQL

10 Hrs

Project on Data filtering the Super store data

10 Hrs





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