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Course / Course Details

Pharma Business Analytics with Python- Elementary

  • Sreenivas BT image

    By - Sreenivas BT

  • 0 students
  • 60 Hours

Course Description

Python plays a crucial role in business intelligence, enabling data manipulation, analysis, and visualization, which are essential for extracting actionable insights and driving data-driven decision-making.


Python provides a robust and efficient framework for handling large datasets and performing complex calculations. Python's data storytelling visualization capabilities allow BI analysts to communicate findings effectively and engage stakeholders. By leveraging Python for analysis and

visualization, businesses can make more informed decisions based on data insights.


Python is a highly sought-after skill in the BI field, offering career advancement opportunities. In essence, Python empowers BI analysts to transform raw data into actionable intelligence, driving better decision-making and business outcomes.

Course Outcomes

What You'll Learn

  1. This course will be the first of its kind ..wherein understanding & learning the analytics will be closely intertwined with learning Python hands-on with real world examples. 
  2. Foundational learning of analytics in this program will be logically leading to mastering Intermediary python and will cater examples from traditional data analytics to image analytics.
  3. Analytics training will not only equip you with expertise but also get  to know how to stitch and connect with other departments at work
  4. On analytics ladder, one will get to know how statistics will be the backbone from descriptive analytics to predictive analytics.
  5. Understanding core programming structures: Audience learn to use variables, data types (integers, floats, strings, etc.), control flow statements (loops, conditionals), functions, and object-oriented programming (OOP)
  6. Data structures: Audience gain proficiency in working with lists, tuples, dictionaries, arrays and other data structures to organize and manipulate
  7. Algorithm development: Audience learn to translate problem descriptions into Python code, using algorithms and data structures to solve problems.
  8. File handling: Audience learn to read and write data from files, a crucial skill for data analysis and other applications.
  9. Debugging and error handling: Audiences develop the ability to identify and correct errors in their code, ensuring the robustness of their programs.

Course Curriculum

  • 14 chapters
  • 0 lectures
  • 0 quizzes
  • 60 Hours total length
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Instructor

Sreenivas BT

With a proven track record in IT infrastructure management and project delivery, Sreenivas BT brings over two decades of expertise to the technology sector. He specializes in cloud solutions, data center operations, and IT service management, consistently driving operational excellence in complex environments. Sreenivas is recognized for his leadership in streamlining processes, optimizing resources, and ensuring seamless technology integration for large organizations. Passionate about leveraging technology for business transformation, he thrives on tackling challenges and delivering measurable results. 

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