connexicatech

  • +977 1 592 6025
  • info@connexicatechnologies.com
  • Tokha -03, Kathmandu, Bagmati, Nepal
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Data Science

Data Science is revolutionizing industries by extracting actionable insights from vast amounts of data. At Connexica Technologies Pvt. Ltd., we leverage cutting-edge data science techniques to help our clients unlock the full potential of their data. From predictive analytics to machine learning algorithms, we empower businesses to make informed decisions, optimize processes, and drive innovation. Our data-driven approach enables us to deliver customized solutions tailored to the unique needs of our clients, ensuring measurable results and sustainable growth in the digital era.

Why to learn Data Science

  1. Gain practical skills for a successful career transition or advancement in the data science field.
  2. Demonstrate expertise in data science concepts to impress potential employers during interviews.
  3. Develop a strong foundation in the mathematical principles supporting Machine Learning, a unique aspect often overlooked by other courses.
  4. Master data preprocessing techniques to ensure data quality and accuracy.
  5. Acquire proficiency in Python programming language for statistical analysis and data manipulation.
  6. Utilize Python libraries such as NumPy, stats models, and scikit-learn to create advanced Machine Learning algorithms.
  7. Apply Python coding to execute linear and logistic regressions, as well as perform cluster analysis and factor analysis.

Have the first mover advantage

Nepal’s low rate of digital adoption – a fact underscored by the World Economic Forum’s Global Competitive Index 2019, which highlighted Nepal’s poor performance in areas of innovation capability as well as Information communication and technology adoption, will make incorporation of Big Data Analytics and BI into organizational processes a herculean task. This preferably needs to be tackled with an all-encompassing collaboration between the public and private sectors since it requires large investments in computational infrastructure in addition to a framework for adoption through policies and laws around data sharing and security.