Overview What You Will Learn Curriculum Instructor

Course Overview

What separates a successful data analyst from the rest? The demand for data professionals is at an all-time high and yet, landing a high-paying data analysis job is as hard as ever. The difference isn’t just technical expertise. It’s the ability to use data to solve real-life business challenges. What’s missing is a structured approach to generating actionable insights from raw data. Data Analysis with Python Masterclass provides you with a framework to do so. 

This course is a stepping stone to a successful career as a data analyst/business analyst. It has been designed for beginners but would be just as helpful to intermediate professionals. 

The course includes two case studies that use the data from the 2020 Kaggle Machine Learning & Data Science Survey to demonstrate how to work with real-world data. In the first case study, we analyze the data to generate insights and build a deep understanding of our data. In the second one, we explore business objectives, dive deep into the dataset, and generate actionable insights. 

By the end of the course, you will be ready to tackle real-life data analysis assignments and fast-track your career.

What You Will Learn

  • Understanding complex data and the art of tackling it.
  • The art of performing data analysis with DA framework
  • Takeaways from this course and the next steps!

Program Curriculum

  • Data Understanding
  • Generating Insights
  • $7 Million Cybersecurity Scholarship by EC-Council
  • Chapter 1 Quiz

  • Structuring Analysis using DA Framework
  • Education
  • Where Do You Work?
  • Job Role and Experience
  • Tools of the Trade
  • Chapter 2 Quiz

What Have We Learned and Where to Go Next?

Instructor

Ankit Shukla

Ankit Shukla is a self-taught data scientist working in the data space since 2014. He is well versed in deep learning, machine learning and Big Data technologies and holds a bachelor’s in engineering from Birla Institute of Technology, Mesra with a major in Biotechnology. His focus areas include Predictive Modelling, Recommender Systems and Natural Language Processing. He is deeply passionate about data science and is always on a look out to give back to the community. His other published works include a paper on developing an enterprise recommender system, 2 papers on Generative Adversarial Networks and the book - Big Data Analysis with Python.

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