• The Institution of

    Data Scientists and Analysts

    PROMOTING SKILLS & EDUCATION IN DATA SCIENCE, ALGORITHM INTELLIGENCE & MACHINE LEARNING

    About us Become A Member
  • Foremost professionals in

    Data Science and Analytics

    Machine Learning and Artificial Intelligence

    About us Become a Member
  • Social Good through

    Artificial Intelligence and Machine Learning

    About us Join Us
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Professional Membership

IDSA peer reviewed professional membership is recognised by leading international organisations. IDSA membership validates your skills, knowledge and experience and can help you take the next steps in your career.

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Professional Certification

If you believe you already have the requisite education, skills and experience to qualify as a professional in your chosen field, you can register for certification and upload evidence of your experience and qualifications.

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Free Courses

If you are not yet ready for certification, we have identified a learning path of online courses with our partners, which are mapped to our requirements for qualification. Should you choose to expand your skills and knowledge...

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About Us

A world of innovative
and dynamic solutions

Our program is designed for IT and non-IT professionals who are interested to transition their career into data science, analytics, machine learning and artificial intelligence

The Institution of Data Scientists and Analysts is a professional and membership-based organization for data scientists, data analysts, data engineers, academics and individuals who show interest in the field. The Institution serves its members, develop and advance the profession of data science, Artificial Intelligence, Machine Learning and Data Analytics, increasing diversity, and advancing ethical data science in Nigeria, Africa and across the globe.

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10+

Partners

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8+

project support

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500+

Membership

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6+

locations

Competence and Skills

Discover new relations
and realise new possibilities

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Statistical Techniques

General statistical analysis techniques and their use for data inspection, exploration, analysis and visualisation (as supporting activity for more complex data analysis)

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Computational Thinking

Apply information technology, computational thinking, and utilize programming languages and software and hardware solutions for data analysis.

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Programming Languages

Use general and specialised statistical and data analysis programming languages and tools to develop specialised data analysis processes and applications.

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Data Visualization

Create and communicate compelling and actionable insights from data using visualization and presentation tools and technologies.

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Data Management

Data collection, data entry and annotation, data preparation, data and files versioning, Data Management Plan (DMP), metadata, Open Data, data repositories

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Research Methods

Create new understandings and capabilities by using the scientific method to discover new approaches to create new knowledge and achieve business goals

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Delivers new capabilities

Bringing transformative benefits
to organizations, businesses and societies

What’s the difference between data science, artificial intelligence, and machine learning?

To better understand data science—and how you can harness it—it’s equally important to know other terms related to the field, such as artificial intelligence (AI) and machine learning. Often, you’ll find that these terms are used interchangeably, but there are nuances. Here’s a simple breakdown:

  • AI means getting a computer to mimic human behaviour in some way.
  • Data science is a subset of AI, and it refers more to the overlapping areas of statistics, scientific methods, and data analysis—all of which are used to extract meaning and insights from data.
  • Machine learning is another subset of AI, and it consists of the techniques that enable computers to figure things out from the data and deliver AI applications.

How data science is transforming business

Organizations are using data science to turn data into a competitive advantage by refining products and services. Data science and machine learning use cases include:

  • Determine customer churn by analyzing data collected from call centers, so marketing can take action to retain them.
  • Improve efficiency by analyzing traffic patterns, weather conditions, and other factors so logistics companies can improve delivery speeds and reduce costs.
  • Improve sales by creating recommendations for customers based upon previous purchases.
  • Detect fraud in financial services by recognizing suspicious behaviours and anomalous actions.

Tools for Data Science

Building, evaluating, deploying, and monitoring machine learning models can be a complex process. That’s why there’s been an increase in the number of data science tools. Data scientists use many types of tools, but one of the most common is open source notebooks.

  • Some of the most popular notebooks are Jupyter, RStudio, and Zeppelin. Notebooks are very useful for conducting analysis, but have their limitations when data scientists need to work as a team. Data science platforms were built to solve this problem.
  • To determine which data science tool is right for you, it’s important to ask the following questions: What kind of languages do your data scientists use? What kind of working methods do they prefer? What kind of data sources are they using?

Membership Categories

IDSA membership validates your
skills, knowledge and experience

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Upcoming Event

Data4Peace

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Webinar Series

The second #Data4Peace Workshop on December 1-2, 2021 "Emerging Technologies in Peacebuilding and Prevention, Lesson Learned from Humanitarian Actors", hosted virtually at the New York University Center on International Cooperation. Focus include the HDX and the OCHA's Centre for Humanitarian Data.

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Fellowship

IDSA honours individuals who have made outstanding contributions to the development of data science, data analytics, artificial intelligence, machine learning, and software development and information technology in Nigeria, Africa and across the globe. There are three different categories of fellowship of the Institution of Data Scientists and Analyst.

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Excellent service & support!!

Understand how to improve data quality, security, privacy, and governance. Know how to embed analytics in your organisation culture – supporting every action, business process and decision.

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Data Visualization and Data Storytelling

Geared to strengthening data visualization and storytelling skills, this short course is designed and delivered in partnership with Vizlogue, Data Visualization and Storytelling Lab. Highly interactive and practical, this short course will expose participants to real-world examples and exercises tailored to the UN context.

Our blog

Some of our latest blog posts

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21 Feb

Data Science Definition

Data science combines multiple fields, including statistics, scientific methods, and data analysis, to extract value from data. Those who practice data science are called data scientists, and they combine a range of skills to analyze data collected from the web, smartphones, customers, sensors, and other sources. Data science is an untapped resource for machine learning. It is one of the most exciting fields...

By: Admin | 21 February 2022
11 Jan

How data science is transforming business

By: Admin | 11 January 2022
17 Jan

Tools for Data Science

By: Admin | 17 January 2022
26 Jan

How to Become a Data Scientist

By: 'Gbenga Adeleye | 26 January 2022

Developing Your Skill in Data Science

Our program is designed for IT and non-IT professionals

  • advantage1

    Be ready to practice data science

    IDSA courses are designed to prepare students for real commercial work in the area of data science, AI and big data.

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    Receive the best training

    IDSA trainers are actively working in the industry and will teach you how to practice data science and advanced analytics.

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    Get more support and guidance

    The member network offers support and guidance from mentors and direct connections to the industry. You will meet employers in-person at IDSA events.

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