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Data Science Explored: Episode 7 of Tech Talk on TRUST TV

**Description:**

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In this video, we dive into the fascinating world of data science. Our guest, Peter Pablo Okukogu, a data scientist and educator, explains the fundamentals of data science and its applications in various industries.

Data science is a multi-disciplinary field that combines statistics, mathematics, computer science, and domain expertise to extract actionable insights from complex data sets. It involves tasks such as data cleaning, statistical analysis, modeling, machine learning, and data visualization. Data scientists use programming languages like Python and R, statistical software like SAS and SPSS, and Big Data Technologies like Hadoop and Spark.

Data science has wide-ranging applications in finance, healthcare, marketing, and e-commerce. It is used for fraud detection, predictive maintenance, customer segmentation, recommendation systems, and much more.

The demand for data science professionals is on the rise in Nigeria, as businesses increasingly rely on data and new technologies to succeed. However, companies face challenges in effectively managing their data science teams and workflows. Without proper centralized management, executives may not see a full return on their investment.

We also discuss the relevance of data science in Nigeria, particularly in Kaduna state. The state government has implemented a data revolution plan, collecting data in various sectors like healthcare and road traffic. Data analysis plays a crucial role in making informed decisions based on the collected data.

Watch the full video to learn more about data science and its impact in Nigeria. Let us know your thoughts in the comments section below.

Keywords/Tags: insecurity, buhari, london, kano, lagos, kaduna, nigeria, minna, ibadan, kogi, jigawa, benin, warri, uyo, portharcourt, rivers, oyo, osun, newyork.

**Sources:**

1. [Data Science Definition](https://en.wikipedia.org/wiki/Data_science)
2. [Python](https://www.python.org/)
3. [R Programming Language](https://www.r-project.org/)
4. [SAS](https://www.sas.com/en_us/home.html)
5. [SPSS](https://www.ibm.com/analytics/spss-statistics-software)
6. [Hadoop](https://hadoop.apache.org/)
7. [Spark](https://spark.apache.org/)

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