Avdhesh Gaur is a Data Analyst, instructor, author, storyteller, speaker, and consultant as well when it comes to bringing insights out of data and visualizing the same. His career spans more than 7 years with a focus on taking down various business requirements by building Data-driven BI models using Tableau, SQL, Hive, and numerous Statistical data analysis Techniques. Avdhesh Gaur got one of his submissions to Tableau accepted on 7th January 2019. On average, only 1 out of every 10000 tableau public profile holders can achieve this feat marking him under the top 0.01% of the profound Tableau Authors, when it comes to creating efficient dashboards with tableau. Even though, He has authored numerous courses covering the fundamentals of data visualization. There was a time when he couldn't figure out, what’s something new that he can do tomorrow. That's why he feels immense joy in creating and sharing the content that can help us learn something new each day. LinkedIn: https://www.linkedin.com/in/avdheshgaur/ Tableau Public: https://public.tableau.com/profile/avdhesh.gaur

Ashwin Pajankar is a Science Popularizer, a Programmer, a Maker, and an Author. He holds a Master of Technology in Computer Science and Engineering from International Institute of Information Technology Hyderabad (IIIT-H). Ashwin has published more than a dozen of books on Python Programming, Test Automation, Raspberry Pi, Computer Vision, Arduino, and Supercomputing with reputed global publishers like Packt, Apress, Leanpub, and BPB. He has earned many professional certifications in the areas of development, administration, and testing from Oracle, IBM, Informatica, Teradata, and ISTQB. He has over a decade of work experience in a few big brands like Cisco Systems and Cognizant in technical roles. He also has worked in a couple of startups in technical leadership roles.

During his 9 years of experience in the field of data science, Jaroslav has worked on many enterprise-level projects, mainly in the marketing and banking domain. He cooperated on a development of a data science platform. His main experience covers data analytics, building data and machine learning pipelines, reporting and its automation, analytic web application development, building production ready predictive models and python development. His approach when working on projects, can be described “build it quick to be wrong, then tweak it to be good enough” and “do not let the perfect be enemy of the good”. He emphasizes continuous advancement in life and learning new things. During his data science learning path, he found, that when learning, most important is to know the foundations, concepts and the possibilities. The remaining things is your own practice, research, and amount of time committed.