Certificate in Business Analytics

Hours of Learning

240 Hours

DURATION

One Year

Mode of Learning

Online

Fees

£ 300

About the Programme

Certificate in Business analytics from ISDC is an IoA endorsed programme. The programme equips the learners with the skills and expertise to build a reputable and high paying career in the World of Analytics. The programme curriculum comprises of 6 core subjects which will develop the foundation towards Business Analytics starting from the basics to advanced level conceptualisation. The modules are Python Programming, SAS and Tableau, Big data analytics, Social Media Analytics, Natural Language Processing, Machine learning and Artificial Intelligence.

Programme Highlights

ioa programme highlights

The Institute of Analytics (IoA)

The Institute of Analytics (IoA) is the UK based professional body for analytics & data science professionals across the world. IoA is a not-for-profit organisation that is committed to advancing the study and application of analytics & data science in society and it exist to promote greater awareness, understanding and innovation in analytics & data science.

The IoA provides members with the opportunity to network with other analytics & data science professionals, learn about career progression, share knowledge and expertise, access Continuous Professional Development programs, and to carry the official designation of the Institute.

By becoming an IoA member, you join the largest community of analytics & data science professionals whilst also keeping your knowledge and expertise up to date with the latest developments and trends that can help you expand your horizon into the ever-evolving world of analytics & data science.

Busines Analytics

Benefits of IoA Membership

Eligibility

Any Commerce or Management Graduate.

Career Prospects

If you’re thinking about a career in analytics, an IoA accredited course will help you achieve your goal.

    • Data Engineer
    • Data Analyst
    • Machine Learning Engineer
    • Data Journalist
    • Database Admin
    • Financial Analyst
    • Business Analyst
    • Product Analyst
    • Business Intelligence Analyst
    • Marketing Analyst
    • Quantitative Analyst
    • Data Visualisation Specialist
    • Functional Analyst
    • Data System Developer

Programme Curriculum

Python Programming module is intended for students who wish to learn the Python programming language. This module is highly important so as to proceed with this programme. The module comprises Programming basics with regards to Python Language such as Data Types, Operators, Functions, Classes and Exception Handling.   

This module forms an introduction as well as an in-depth study in the discipline of SaS programming with regards to Statistical Analysis along with Data Visualisation through Tableau. The module comprises basic introduction and programming in SaS, using Procedures within SaS and Data Visualisation using Tableau application. 

This module forms an introduction as well as an in-depth study in the field of Big Data and Hadoop. It comprises of the fundamentals as well as advanced topics needed to progress in this technology. The students will learn about the applications, usage and several use case scenarios pertaining to Big Data- Hadoop where they can use the knowledge and progress ahead.

This module comprises of advanced disciplines and units pertaining to Analytics, Data Acquisition via web, Understanding and analysing Unstructured Data along with the future implementations and growth in the discipline of Analytics. 

The following module aims to provide an exposure to students based on Natural Language Processing Techniques, Algorithms and Analytics based on Textual Data. The module comprises of NLP basics, Feature Extraction, Relationship Extraction, Text Categorisation, Clustering and Topic Modelling Algorithms and Practices. 

This module comprises of conceptual, statistical and Machine Learning algorithms. It covers all the necessary models pertaining to Machine Learning such as Regression, Decision Trees, Support Vectors, Clustering, Association Analysis and Dimensionality Reduction.

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