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Day 2
Skills Learnt today
Introduction to Data Slicing & Dicing in Excel
Use of Pivot tables feature to slice & summarize data
Use of Filters and Slicers to drill down datasets
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Five Skills & You become a Data Analyst
1. Critical Thinking
2. Hypothesis Formation & Testing
3. Data Cleansing
4. Mathematics (Stats, Calculus, Algebra, Probability)
5. Data Visualization
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Day 124
Major progress on a jupyter notebook to benchmark feather format VS pandas and native pandas vs python functions.
Some super fast speed ups already.
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Day 12&13
Finished datacamp's importing data in Python lecture. Dealt with various data sources such as SQL,htfm5(?) ,Excel sheets and others. Really need to pick up more speed...
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Day 11
Finished the exercises for week1 of the Georgia tech lecture, got more familiar with the basics manipulation of data types, especially on dictionaries.
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Day 111
Continuing work on Spark. Got AWS EC2, EMR, and S3 up and running, along with a basic notebook in Databricks.
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Day 10
Today i began my journey into @GeorgiaTech 's "intro to computing for data analysis" course on edX, spent most of the time reviewing basics of different data types. Plus I learnt about techniques such as .format () and assert.
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Day9
Today I finished @DataCamp 's intro to database in python and touched upon basic SQL queries using the sqlalchemy package. I learned basics such as group_by,sort_by and insert. With that i have finished the data manipulation track.
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Day 107
Continuing to build a reviews sheet that encompasses Pandas, NumPy, Scikit-learn, and some basics of ML and Tensorflow.
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Day 4 +Day 5
In these two days I did a small project on Data camp using data manipulation and merging data techniques. Some methods included are : merge ();reset_index();.melt
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#Erniecoding
This is my account for murmurs on studying programming & Data Science after repeated failure, let's hope this time will be better. Loll #100DaysOfCode #100daysOfDS
Day 46/100
Reviewed some basic dataframe wrangling and manipulation.
Data analysis of the results from unit testing.
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Day 45/100
Stumbled through another code challenge on arrays.
Refactored and cleaned up several scripts. Wrote a couple draft READMEs for future teams. Don't want them in the position we were - aimlessly wandering code the first week.
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Day 19/100
2 more code challenges this morning.
Really interesting presentation on UX design basics from @thedavid.
Got working on some tests to establish a baseline for our first release canvas.
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Day 13/100
Another Python code challenge.
Working on a Product Release Canvas for our upcoming sprints. Spent a lot of time reviewing code from previous groups. Amazed at how much I'm able to understand.
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Day 11/100
More Python code challenges on @hackerrank.
More @LambdaSchool Labs orientation.
Getting there. Slowly.
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Day 10/100
Python practice in the morning and then spent all day in @LambdaSchool Labs orientation. Well done @RyanleeHamblin & @party_shah!! TONS of info, but great job setting expectations and getting us all on the same page (hopefully so 🤣)
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Day 9/100
Spent a good chunk of today getting in the Python practice reps:
- code challenges on @hackerrank
- watching some @CoreyMSchafer
videos
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Day 8/100
Continuing to work thru a @udemy
course on building and deploying an ML pipeline. Had some hiccups working with Flask and @heroku, but eventually got it deployed.
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Day 7/100
Working thru a @udemy
course on building and deploying an ML pipeline. Really interesting to see a lot of what I've been learning coming together.
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