Kickstarting a career in data - Sharing some tools, tips, tricks and resources
- 1. Kickstarting a career in data Tools, tips, tricks and resources
- 3. Mathematics/statistics, Programming, Data ● Similarity
- 4. What is data https://www.worldometers.info/world-population/population-by-country/
- 6. What can you do with data? ● Describe ● Infer
- 7. ● Data Analytics - Descriptive Statistics ● Data Engineering ● Data Science - Inferential Statistics
- 8. Descriptive Statistics - Analytics ● When and Why these? ○ Spreadsheet ○ Sql ○ Looker Studio / Tableau / PowerBI ○ Python ○ Colab
- 10. Why Programming Skills Can be of help in Analytics? Data Wrangling
- 11. Why Programming Skills Can be of help in Analytics? Data Wrangling
- 12. Analytics ● Spreadsheets ○ cell, ○ Sheet, ○ basic formula, ○ referring cells from one to another ○ Sum, count, average, ○ Basic charts - bar, pie ○ If, countif, if else, ○ Look ups - v and h look ups ● Databases ○ Select ○ DMLs ○ Joins ○ CTEs ○ Window functions ● Python ○ Basic python ○ Use of Libraries - Pandas ● Visualisation ○ Basic plots
- 13. Trick time… Colab and Why Colab? A quick demo - Use this to work on your python skills https://colab.research.google.com/
- 14. Colab - Quick Demo
- 15. Data Engineering
- 16. Data Engineering ● Sql ● Python ● GCP or AWS (Our focus - Biquery) ● Google certifications - https://www.cloudskillsboost.google/paths
- 17. Trick Time again - Bigquery - Sandbox Use this to practise your sql skills 1. Creating a data set 2. Creating a table 3. Importing a csv 4. Complex data types Things to try out: 1. JSON, string functions, JSON functions
- 18. Data Science - Inferential ● IIT Madras - Data Science and Programming ● Coursera - Andrew Ng’s machine learning course
- 19. Resources - Jump in ● Udacity - Machine learning nano degree (pros and cons) ● Abirami Sukumaran’s Code Vipassana Sessions - https://sites.google.com/view/cv7a
- 20. Thank you! Thank you, GDG Kozhikode! ❤