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PG Diploma in Business Intelligence
This course provides an overview of the technology of Business Intelligence (BI) and the application of Business Intelligence to an organization’s strategies and goals.
Batch starts date

May 8, 2023

Program Duration

9 Months

Learning Format

Blended Learning

Program Fees

$4250

Course Overview

Business Intelligence (BI) refers to technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. The purpose of business intelligence is to support better business decision-making. This course provides an overview of the technology of BI and the application of BI to an organization’s strategies and goals.

Training Key Features

For More Information

    What you will learn

    About UCAM

    Universidad Católica de Murcia (UCAM), founded in 1996, is a fully-accredited European University based out of Murcia, Spain. With learning centres in the Middle East and Southeast Asia, UCAM aims to provide students with the knowledge and skills to serve society and contribute to the further expansion of human knowledge through research and development.

    The university offers various courses, including 30 official bachelor’s degrees, 30 master’s degrees and ten technical higher education qualifications through its Higher Vocational Training Institute, in addition to its in-house qualifications and language courses. The programmes offered are distinguished in Europe and worldwide, with good graduate employability prospects as well.

    UCAM is accredited by ANECA (National Agency for Quality Assessment and Accreditation of Spain) and the Ministry of Education regarding 17 of its undergraduate degrees.

    Airtics Education’s PG Diploma Programs are certified by UCAM University.

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    Skills Covered

    Word2vec

    Machine Translation

    Sentiment Analysis

    Transformers

    Attention Models

    Word Embeddings

    Locality-Sensitive Hashing

    Vector Space Models

    Parts-of-Speech Tagging

    N-gram Language Models

    Autocorrect

    Who Can Apply for the Course?

    Tools/ Frameworks/ Libraries

    Application And Use Cases

    Logistics and Delivery
    Web Search or Internet Web results
    Search Autocorrect and Autocomplete
    Customer segmentation
    Personalised Marketing
    Financial trading
    Marketing personalization
    Recommendations

    Eligibility

    Firm knowledge of software fundamentals with data structures, linear programming and architecture are beneficial. Candidates from programming and non-programming backgrounds could also opt for this in-demand course.

    Prerequisites

    Basic understanding of computer technology.

    Course Modules

    • Python basics
      • Variable and data types
      • Conditional statements
      • Loops
      • Functions
    • Python Libraries
      • Numpy
      • Pandas
      • matplotlib
    LEARNING OUTCOMES
    • Learning python structure and how to write programs in it.
    • Basic concepts of Python, its syntax, functions, and conditional statements.
    • Acquire the prerequisite Python skills to move into specific branches – Machine Learning, and Data Science.
    • Understand packages to enable them to write scripts for data manipulation and analysis.
    • Linear algebra
    • Probability
    • Statistics
    • Data Cleaning
    • Data Pre-processing
    • Statistical tools
      • CSV
      • Excel
    LEARNING OUTCOMES
    • Introduce statistical tools for working with datasets
    • Learn the essentials of probability and statistics for data analysis & visualization.
    • Know how to import and clean data using libraries like NumPy and Pandas for data exploration and analysis.
    • Learning to fix incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset.
    • Data visualization introduction
    • Types of charts
    • SQL and Databases
    • SQL commands
    LEARNING OUTCOMES
    • Acquire a fundamental understanding of the analytical techniques and software tools necessary to effectively generate useful information from structured and unstructured datasets of any size CHARTS
    • Gain experience in using the tools and techniques of data science to structure and complete projects focused on obtaining actionable insights from complex data
    • Dive deeply into a chosen area of practice to fully prepare to use the knowledge gained in the program to add significant value in a professional setting
    • Be able to utilize knowledge and skills to continue learning and adapting to new data science technologies
    • PowerBI
    • Tableau
    • Plots
    • Making Report Views
    • Data Visualization
    • Tableau Query Editor
    LEARNING OUTCOMES
    • how powerbi is helpful land what is business intelligence.
    • data loading and data sources loading into powerbi
    • different types of data visualizations
    • Plots/Chart in powerBI.
    • Dashboard development using a real dataset
    • TABLEAU’s Data, Model, and Report views
    • learn how to shape and transform your data before the data analysis using Tableau Query Editor.
    • How to filter the information in your reports by location and control how these filters interconnect and interact with other visuals in your report.
    • Data understanding
    • Data preparation
    • Data Modeling
    • Identifying Patterns
    • Data warehousing
    LEARNING OUTCOMES
    • Discuss the fundamental data mining concepts such as classification, clustering, regression, and unsupervised learning.
    • Introduction to data mining algorithms
    • Understanding the data mining process and techniques
    • Engaging in meaningful discussions about pattern evaluation metrics and investigating techniques for mining various patterns, including sequential and sub-graph patterns.
    • Introduction to machine learning
    • Supervised Learning
    • Unsupervised learning
    • ML Deployment
    LEARNING OUTCOMES
    • You will learn about training data, and how to use a set of data to discover potentially predictive relationships.
    • Understand basic concepts and common tools used in machine learning.
    • you will master machine learning techniques, including supervised and unsupervised learning and hands-on modeling, rounding out your artificial intelligence education.
    • learn popular machine learning algorithms, Feature Selection, and Mathematical intuition behind it. L05.Learn the basics of the HTML/CSS, and Git version control system (VCS). L06.Build and Deploy a model to enable WebView.

    Interested in This Program? Secure your spot now.

    The application is free and takes only 5 minutes to complete.

      Student Reviews

      Veeraiah Yadav Doddaka
      IT Manager, Samsung

      I choose to learn Data Science and explored many options on which institute to join, among that what I found is Airtics as the best in terms of the course curriculum/on line content they designed and most…..

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      Prasad Joshi
      RF Optimization Engineer, Nokia

      I was a Data Science student at Airtics Education, which helped build a solid data science background and sharpen my programming skills…

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      Mohamed Hanan
      Procurement Assistant

      The program in Data Science offered by Airtics Education is rigorous and has provided me with a greater understanding of the data science world…

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      Capstone Projects

      Predicting Sales of a Supermarket Chain

      Classification of Loan Applications

      Marketing Campaign Insights Analysis

      Career Support

      Frequently Asked Questions

      As for the job outlook, according to the US Bureau of Labor Statistics, the demand for qualified BI analysts and managers is expected to grow to 14% by 2026 with overall data professionals to rise to 28% by 2020. Also, according to Bereo Inc., the BI market is expected to grow at a CAGR of 7.6% in 2020.

      With the expansion of the business intelligence field, it is no longer limited to analysis. As more domains have started to adopt business intelligence, various subsets have emerged:

      • Business Analyst: These analysts mine and collect data in multiple ways using the software. And then analyse the same on the industry trends and competitors in order to evaluate and communicate it with upper-level professionals.
      • Business Intelligence Project Manager: A BI project manager establishes the plans for a project after consulting other professionals. These project plans usually define requirements, schedules, and resources.
      • Business Intelligence Specialists: The specialists monitor strategic design and the maintenance of BI activities.
      • Business Intelligence Consultants: These consultants apply BI solutions and manage projects for various clients.
      • Business Intelligence Director: A BI director will be leading the design and development of business intelligence activities for the organization.

      With BI getting more prominent, there has been a rise in confusion between business intelligence (BI) and business analytics (BA).

      By definition:

      Business Intelligence: It uses past and present to drive current business needs.

      Business Analytics: Analyses only the past data to drive current needs.

      Usage:

      Business Intelligence: Runs current business operations.

      Business Analytics: Changes business operations and improves productivity.

      Ease of Operations:

      Business Intelligence: For current business operations.

      Business Analytics: For future business operations.

      Field:

      Business Intelligence: BI comes under Business Analytics.

      Business Analytics: Contains data warehouse, information management etc.

      According to various job portals; the average salaries of various BI job roles in India are:

      • BI Analyst- ₹ 7,90,532 per year
      • BI Manager- ₹ 10,07,544 per year
      • BI Specialist- ₹12,81,082 per year
      • BI Consultants- ₹10,76,000 per year
      • BI Director- ₹30,00,000 per year

      What is included in this course?

      I’m Interested in This Program

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        PG Diploma in Business Intelligence


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