Advanced Certification Program in Data Analytics

BY
EduBridge

Learn data analysis, data visualisation, Python, R, and other analytics technologies and get hired by the best firms in India with this course by Edubridge.

Mode

Online

Duration

658 Hours

Fees

₹ 85000 94000

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based
Frequency of Classes Weekdays
Learning efforts 35-40 Hours Per Week

Course overview

The Advanced Certification Program in Data Analytics course offered by Edubridge is a  110% money-back job-guaranteed program that helps the aspirants to grow and develop in the competitive IT industry with the required technical and professional skills and transform into data analytics professionals.

The Advanced Certification Program in Data Analytics by  Edubridge offers in-depth theory and practical information that has been developed by highly qualified experts across the data science spectrum.

The Advanced Certification Program in Data Analytics training ensures to help learners enhance their comprehension of the industry and the business through guest lectures, and industry immersion events, along with industry-based capstone projects where one can cooperate, learn, and create real-time case studies with cutting-edge technologies. 

The highlights

  • Duration: 658 hours
  • Online course
  • Zero cost EMI facility
  • Average Salary-2 to 8 LPA
  • Job guaranteed program

Program offerings

  • Projects
  • Practical assignments
  • Case studies
  • Y
  • A digital certificate of achievement
  • Dedicated placement manager
  • 1 on 1 mentorship
  • Edubridge job portal access
  • Linkedin profile review
  • Careers fairs
  • And guest lectures

Course and certificate fees

Fees information
₹ 85,000  ₹94,000
certificate availability

Yes

certificate providing authority

EduBridge

Who it is for

This course is meant for fresh graduates from all engineering streams, BCA, MCA, BSc, MSc, or any other degree, and working professionals who aspire to become data analysts.

Eligibility criteria

Educational Qualification

This course is open to all engineering streams, BCA, MCA, BSc, MSc, or any other degree from a recognised university with a major in mathematics or statistics and a score of 50% or higher. Good communication skills are required as the session will be conducted in English.

Infra Requirements

  • Webcam-equipped laptops and desktops 
  • Ideal configuration: 500GB HDD and 8GB RAM
  • Internet speed: more than 4 MBPS
  • No cell phones are permitted.


Advanced Certification Program in Data Analytics Qualifying Details
Candidates will get a Certificate of Achievement after meeting the attendance requirements (85% of training sessions and 100% of placement counseling meetings) and passing the tests with a score of at least 50% in the Advanced Certification Program in Data Analytics.

What you will learn

Following completion of the Advanced Certification Program in Data Analytics syllabus, participants will learn data visualization tool Tableau programming languages, VBA programming language, machine learning, and predictive analytics, etc.

The syllabus

Fundamentals of probability & statistics

  • Course overview
  • Project assignment Statistics
  • Introduction to Statistics
  • Methods/Types of Statistics
  • Other Basic concepts
  • Importance of statistics
  • Probability for data analytics
  • Capstone Project Discussion

Introduction to Data Analytics

  • What is Data?
  • Data Analytics overview
  • Types of Data Analytics
  • Data Analysis Overview
  • Process of Data Analysis
  • Role of a Data Analyst
  • Activity: Migrant & Seasonal Head Start
  • Technical Assistance Centre-Hand
  • Book Data Analysis

Project Presentation and guidance

  • Book Review: Statistical Data Analysis

Predictive Analytics

  • Predictive analytics-Overview
  • Simple Linear regression, Multiple linear regression & Logistic regression
  • Decision Trees and Unstructured data analysis
  • Forecasting and Time series Analysis
  • K means cluster analysis for Indian liver
  • Sales prediction using partitioning tree method
  • Classification model for thoracic surgery data
  • Fertility data analysis with R
  • Breast tissue analysis using KNN
  • Forecasting infant mortality rate in India with time series
  • Predictive model for Diabetic
  • Retinopathy Debrecen data

Fundamentals of Python programming for Analytics

  • Introduction to Python
  • Activity- Python features
  • Python features Lab Activity
  • Environment Setup and setting path
  • Python Environmental Variables
  • Running Python
  • Lab Activity - First Python program
  • Python Identifiers
  • Reserved Words
  • Python Variables
  • Standard Data Types
  • Sets
  • Frozen set
  • Data Type Conversion
  • Python Basic Operators
  • Decision Making, Loops, Python Functions & Modules
  • Files- I/O, Directory and File Management
  • Python Errors & Exception Handling
  • Python OOPS, Constructors, Inheritance
  • Polymorphism, Encapsulation and Data Abstraction
  • Multi-threaded Programming
  • Assignment 2: Project:
  • Churn E-Mail Inbox with Python

R Programming

  • Python Libraries Introduction
  • Pandas, NumPy, Data operations
  • Data Cleansing, Data Processing, Data Wrangling
  • Data Visualization/ Statistical Analysis of Data using Python
  • Activity – Solo Learn App
  • Project assignment: Building Spam
  • Classifier using Python
  • R – Overview
  • Lab Activity - Installation of R
  • Data Types
  • Lab Activity - Data Types- Vector
  • Data Types- List
  • Data Types- Matrices
  • Lab Activity - Data types List and Matrices
  • Data Types Arrays
  • Data Types - Data Frames
  • Lab Activity - Data Types- Arrays & Frames
  • Variables
  • Lab Activity - Variables
  • Operators
  • Lab Activity - Operators
  • Decision Making
  • Lab Activity - Decision Making
  • Loops
  • Lab Activity Time- Loops
  • Apply, Lapply, Sapply, Tapply in R
  • Lab Activity - Apply,
  • Lapply, Sapply, Tapply in R
  • Functions
  • Lab Activity - Functions
  • Packages & Data Reshaping
  • Lab Activity - Packages & Data Reshaping
  • Data Interfaces
  • Lab Activity - Data Interfaces
  • Data Visualization
  • Statistical Analysis Using R- Mean, Median and Mode
  • T- Test in R: One Sample & Paired

Project Presentation

  • Python-Advanced Python -Project Presentation
  • Overview of Machine Learning
  • Machine learning Project Presentation
  • Dashboard making with Excel

Introduction to machine learning and its algorithm

  • Types of Machine Learning Algorithms
  • Introduction to Machine Learning with Python
  • Supervised Learning Algorithms
  • Unsupervised Learning Algorithms
  • The math of Intelligence
  • Artificial Intelligence vs Machine Learning
  • Natural Language Processing
  • Project: ML-Noise removal from images using Python

Hands-on Machine Learning

  • Implement and demonstrate the FIND-S algorithm
  • Candidate-Elimination algorithm
  • ID3 algorithm
  • Backpropagation algorithm naïve Bayesian classifier
  • Bayesian Network
  • k means algorithm
  • k-Nearest Neighbour algorithm
  • Locally Weighted Regression algorithm

Introduction to Scala

  • Introduction to Scala, Variables, Data Types
  • Program structure, Operators and Inference
  • Strings, Strings formatting and interpolation, String Methods
  • Conditions and loops, Classes and objects, Classes and multiple constructors
  • Closures, Collections overview, Sequences and set, Tuples and map
  • Array, declare an array, declare an array with range, Declare a list of Strings
  • Map of chart, int, declaring a tuple, Declare an iterator, File IO
  • Higher order functions Interaction with Java, Case classes and Pattern matching

Machine Learning with Spark

  • Spark n cluster
  • Advanced spark programming
  • Machine learning with Spark
  • Graph processing with Spark
  • Project-Writing spark applications

Data Analytics with Excel

  • Sorting Data
  • Filtering Data
  • Split Window and Freeze Panes
  • Charts in MS Excel
  • Activity
  • Lab Activity - Pivot Tables, VLOOKUP, SPARKLINE in Excel, SUMIF function in Excel & Excel ISBLANK function in Excel
  • CSV vs Excel (.xls) - What's the Difference?
  • Assignement5: Dashboard making with Excel

VBA in EXCEL

  • Creating a macro
  • Workbook and Worksheet object
  • Range Object, variable, If then statement
  • Loop, Macro Errors, String manipulation
  • Date ,Time & Events
  • Array
  • Function and Subfunctions
  • Application object
  • ActiveX controls
  • User form

SAS - For Beginners

  • SAS- Overview
  • SAS Environment Installation
  • SAS Studio
  • Lab Activity Time - SAS Environmental Installation
  • SAS- Program Structure
  • SAS: Data Sets
  • Lab Activity - Statistical Structure & Data Sets
  • SAS: Variables
  • Lab Activity Time - SAS Variables
  • SAS: Strings
  • SAS: Arrays
  • Lab Activity - SAS Strings & Arrays
  • SAS: Numeric Formats
  • Lab Activity - SAS Numeric Formats
  • SAS: Operators
  • SAS: Loops
  • SAS: Decision Making
  • SAS: Functions
  • SAS: Input Methods
  • SAS Macros
  • SAS: Date & Time
  • SAS: Reading Raw Data
  • SAS: Merge Data sets
  • SAS: Subsetting Data sets
  • SAS: Sorting Data sets Format Data sets
  • SAS: SQL
  • SAS: Output Delivery System
  • SAS: Simulations
  • SAS: Data Visualization
  • SAS: Enterprise Guide
  • Visual Analytics
  • JMP Lab
  • Activity after completion of every topic

Data Visualisation with Tableau

  • Introduction to Visualization and Tableau
  • Tableau essentials & creating visualisations in Tableau
  • Filter groups and sets
  • Formulas in Tableau
  • Level of detailed expressions
  • Optimizing tableau performance
  • Advanced visualization in Tableau
  • Connecting to different data sources
  • Hands-on with Tableau

Capstone Project

  • Data visualization or machine learning model implementation

Admission details

To enrol for Advanced Certification Program in Data Analytics classes, students may follow these steps: 

Step 1: Follow the official URL

https://www.edubridgeindia.com/courses/OTkx/data-analytics-course

Step 2: The applicants must therefore enlist on the Edubridge website.

Step 3:  Unless they can signup and log in, applicants won't receive enrollment confirmation.

How it helps

The Advanced Certification Program in Data Analytics benefits all participants as they will gain communication skills and aptitude skills, learn techniques of teamwork through collaborative projects and in-class assignments, and get a certificate. 

FAQs

Who will award the certificate upon successful completion of this online course?

Edubridge will award the certificate upon successful completion of this online course

Who is this course meant for?

This course is meant for fresh graduates from all engineering streams, BCAMCABScMSc, or any other degree, and working professionals who aspire to become data analysts

What are the programming language and the tools covered in this online course?

Apache Hadoop, Excel, Python, R Programming, SAS, and tableau are the programming language and tools covered in this online course.

What are the benefits provided by this Advanced Certification Program in Data Analytics online course?

Dedicated Placement Manager, 1:1 Career Mentoring, LinkedIn Profile Review, Access to the EduBridge Job Portal, Career Fairs, and Guest Lectures are the benefits provided by this online course.

How do the participants enhance their skills with this program?

The participants enhance their skills through hands-on projects, practical assignments, case studies, communication skills, aptitude skills, resume writing sessions, mock tests, assessments, and interviews with this program.

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