34. Data Analytics - Google Data Analytics Capstone Case Study - Week 2

 Pick a track to make a case study.


Track 1:

    Demonstrate job skills for future interviews

Track 2:

    Flexible portfolio piece about a personal interest


Additional Resources:

https://medium.com/search

https://github.com/search

http://public.tableau.com/

https://www.kaggle.com/


Comments

Post a Comment

Popular posts from this blog

20. Data Analytics - Analyze Data to Answer Questions - Week 1

Goal of analysis is to identify trends and relationships within data so you can accurately answer the questions you're asking. Most data is organized in tables, always have data in the right format. Definition : Analysis // process used to make sense of the data collected Sorting // involves arranging data into a meaningful order to make it easier to understand, analyze, visualize Outliers // data points that are very different from similarly collected data and might not be reliable values Filtering // extracting specific data that meet certain criteria while hiding the rest Customized sort order // when you sort data in a spreadsheet using multiple conditions The 4 phases of analysis:          1. Organize data // getting the right data in the right size and order                     - Sorting : arrange data in meaningful order              ...
Read more

2. FreeCodeCamp - Dynamic Programming - Learn to Solve Algorithmic Problems & Coding Challenges

Dynamic Programming - Parts      PART 1 - Memoization     P ART 2 - Tabulation Dynamic Programming with Fibonacci Example Recursion: Slow because time complexity is O(2^n) func fibR (x int ) int {     if x <= 2 {         return 1     }     return fibR (x- 1 ) + fibR (x- 2 ) } Dynamic Way Example Recursion with Stored Value:  // Fast because it removes duplicate processes by checking map. // Tail recursion-ish // Results are hitchhiking each recursive call func fibR2 (x int , y map [ int ] int ) int {     if _ , ok := y[x]; ok {         return y[x]     }     if x <= 2 {         return 1     }     y[x] = fibR2 (x- 1 , y) + fibR2 (x- 2 , y)     return y[x] }
Read more

5. SQL Injection - Blind SQL Injection

These SQL Injects is when query does not return results back in their HTTP responses, so UNION attacks are not useful. Blind SQL Injections can be exploited using conditional responses. Example, if we figure out that a website reacts a certain way when a valid cookie is sent then we can add onto the HTTP request to ask application/database True/False questions. If there are no answers to our question, then the website whatever "True" response to the valid cookie will not show. If there is an answer, then the response will show. Using "and" on the "WHERE" clause to add our additional conditional request. Lab 11 - Blind SQL injection with conditional responses Vulnerable parameter - tracking cookie End Goals: 1) Enumerate the password of the administrator 2) Log in as the administrator...
Read more