iLearner:


Thank you very much for this. I just enrolled in the Data Science Lab and started. When ASUU finally allows me finish my Statistics degree this year, I'll definitely be giving the MSc a shot

please how is the test? I at that stage now I really want to scale through and be admitted. Kindly help with tips

Emmyxclusive:
please how is the test? I at that stage now I really want to scale through and be admitted. Kindly help with tips

It's easy. Very basic Statistics, maths and python

obalala:
Im still an entry level data analyst so I don't know it all, just practice practice if possible everyday if possible.
Then pick up a certification, that will boost up your chances. Then start applying like mad. Got over 50 rejection till one clicked . Watch a lot of YouTube interview training also cos it seems their interview questions and answers formats is quite different from 9ja .

Good morning Big bros. I have been following the Coursera course and I notice they use public dataset on google icloud & Bigquery for practice. Previously, I learnt SQL basics using PostgreSQL and want to be consistent with it. Is there any way I can download the public datasets on google icloud/Bigquery to upload on Postgress for practice? I have searched google, found no helpful tips yet.

dbeautyful:
Hi temitayo,

So I started this course about 3 months ago going through everything especially the tests. I work with spreadsheet and powerpoint a lot, but was a social science student in University. That's why I'm careful not to skip any thing.

Unfortunately, if I continue at this pace, I may never finish this course. I have a 9-5 job and other side hustles.

So my question is are there any penalties for skipping Discussion Prompts and Self-Reflection: see example below.
I am trying to get past all these and get down to the technical stuffs like sql, tableau, R etc.

Please advise.

It is not compulsory to use the discussion prompts. For self reflection, since its graded, you can just write a sentence then submit it. That is what I do. I am on the same course.

I recommend Jupyter Notebook. Pycharm is can be slow.

Bibitayo2:
Good morning everyone
Pls, which IDE is the best for data analysis between this two? Pycharm and Spyder.

This is why I prefer Jupyter notebook. You wouldn't need to use print statement

Yutes:

Same thing didn't show the table

are you sure you are in the right folder directory?
Or better still try replacing 'train.csv" with whatever path you have , e,g for windows "c:\windows\username\ xxxxxxxxxxxxxxxx\ train.csv"

jackcanfield:

import pandas as pd
e = pd.read_csv( "train.csv" )
print(e)


make sure you install openpyxl and pandas correctly.

Hmm, would be difficult. Just try to download the csv or tar.gz files and import to your database. I use PgAdmin.

Now what you seek to achieve , I can achieve with Kaggle api (import opendatasets as od ) to download datasets and to explore with Pandas on Jupyter notebook

Omotaday:
Good morning Big bros. I have been following the Coursera course and I notice they use public dataset on google icloud & Bigquery for practice. Previously, I learnt SQL basics using PostgreSQL and want to be consistent with it. Is there any way I can download the public datasets on google icloud/Bigquery to upload on Postgress for practice? I have searched google, found no helpful tips yet.

Whynow:
are you sure you are in the right folder directory?
Or better still try replacing 'train.csv" with whatever path you have , e,g for windows "c:\windows\username\ xxxxxxxxxxxxxxxx\ train.csv"

lol I already ran and it printed out, was just explaining to someone what to do.. but I am using the Python IDLE perhaps you are using a Power Shell.

iLearner:


It's easy. Very basic Statistics, maths and python

Thanks, I put in on hold before for proper preparation

Whynow:
This is why I prefer Jupyter notebook. You wouldn't need to use print statement

I switched to jupyter

Whynow:
Hmm, would be difficult. Just try to download the csv or tar.gz files and import to your database. I use PgAdmin.

Now what you seek to achieve , I can achieve with Kaggle api (import opendatasets as od ) to download datasets and to explore with Pandas on Jupyter notebook

Thanks bro, will try that

Thank you.

Omotaday:
It is not compulsory to use the discussion prompts. For self reflection, since its graded, you can just write a sentence then submit it. That is what I do. I am on the same course.

Raalsalghul:


Start with SQL (Over 95 per cent of Data Analyst roles require this skill). There are many RDBMS you can use to learn but MySQL is the most common.

Then learn Excel with emphasis on (Look-up and Statistics functions, referencing, conditional formatting, power query for cleaning data, pivot tables for summarizing data, power pivot for modelling and then DAX).

Followed by PowerBI or Tableau: you'll use these tools to visualize the results of your SQL queries. I personally prefer PowerBI as it's more robust in function.


People mention Python a lot, but I've seen many Data Analyst vacancies excluding it in their requirements (emphasis on "Data Analyst"). Nonetheless you can add it to your skill set if you want to go the Data Science Route or just for personal development purposes. Learn the basics first and then move on its libraries: Numpy, Pandas, Matplotlib and Seaborn. There's also the Scikit learn library for its machine learning capabilities.

If you can master the first 3, you're job ready: then scale up your knowledge from there.

What's up guys? I know it's been long since I posted here: been busy with going back to school, work and other stuff.

I remember giving the above advice the last nine months and I'll like to say that as of today, it still stands most especially from my experience working as a data analyst with an NGO while doing my MSc.

I can't emphasize it enough: learn your SQL. Again I repeat, learn your SQL if you are to switch to anything data related: whether a data analyst, scientist or engineer.

Most organizations have databases which you'll use SQL to interact with. I'm saying this because sometimes I feel there's too much emphasis on learning Python. Don't get me wrong; python is important in the world of data but it should be like number 4 on your learning list with spreadsheets and BI tools before it.

In addition to the above, I would advise you work with larger databases when practicing: the table I've been working with had about 120000 rows by 220 columns and it was just one table out of about 300 Quite large when you compare it to the ones used on your Udemy tutorial or YouTube or even Kaggle.

I'm not saying this to discourage anyone, just giving you an insider perspective. I would post more tidbits when I have the time.

Raalsalghul:


What's up guys? I know it's been long since I posted here: been busy with going back to school, work and other stuff.

I remember giving the above advice the last nine months and I'll like to say that as of today, it still stands most especially from my experience working as a data analyst with an NGO while doing my MSc.

I can't emphasize it enough: learn your SQL. Again I repeat, learn your SQL if you are to switch to anything data related: whether a data analyst, scientist or engineer.

Most organizations have databases which you'll use SQL to interact with. I'm saying this because sometimes I feel there's too much emphasis on learning Python. Don't get me wrong; python is important in the world of data but it should be like number 4 on your learning list with spreadsheets and BI tools before it.

In addition to the above, I would advise you work with larger databases when practicing: the table I've been working with had about 120000 rows by 220 columns and it was just one table out of about 300 Quite large when you compare it to the ones used on your Udemy tutorial or YouTube or even Kaggle.

I'm not saying this to discourage anyone, just giving you an insider perspective. I would post more tidbits when I have the time.

Thanks very much for your insight. Do you not mind if I connect with you? I'm a final year Statistics student and since ASUU has refused to allow me graduate, I've been getting busy with a lot of data stuff and would really need a mentor.

iLearner:


Thanks very much for your insight. Do you not mind if I connect with you? I'm a final year Statistics student and since ASUU has refused to allow me graduate, I've been getting busy with a lot of data stuff and would really need a mentor.

Uhmmmm mentorship? Not sure I can take on that right now but you can send me a P.M and I'll answer as much questions as you want.

Yutes:
Just going through this thread and noticed that so many comrades who started the {data: [ analysis, science]} journey in 2020 have dropped by the wayside

Are you a data analyst?

Raalsalghul:


Start with SQL (Over 95 per cent of Data Analyst roles require this skill). There are many RDBMS you can use to learn but MySQL is the most common.

Then learn Excel with emphasis on (Look-up and Statistics functions, referencing, conditional formatting, power query for cleaning data, pivot tables for summarizing data, power pivot for modelling and then DAX).

Followed by PowerBI or Tableau: you'll use these tools to visualize the results of your SQL queries. I personally prefer PowerBI as it's more robust in function.


People mention Python a lot, but I've seen many Data Analyst vacancies excluding it in their requirements (emphasis on "Data Analyst"). Nonetheless you can add it to your skill set if you want to go the Data Science Route or just for personal development purposes. Learn the basics first and then move on its libraries: Numpy, Pandas, Matplotlib and Seaborn. There's also the Scikit learn library for its machine learning capabilities.

If you can master the first 3, you're job ready: then scale up your knowledge from there.

Is SQL different from MySQL?

dunsin125:
Is SQL different from MySQL?

Well, let me explain it like this.

SQL is the language used to communicate with databases in relational database management systems

MySQL is an example of a relational database management system same as Google Big Query, MSSQL, SQLlite, Oracle etc

In short, let me put it this way: MySQL like others mentioned is just a platform while SQL is the language used in these platforms.

Hope that suffices?

Raalsalghul:


Well, let me explain it like this.

SQL is the language used to communicate with databases in relational database management systems

MySQL is an example of a relational database management system same as Google Big Query, MSSQL, SQLlite, Oracle etc

In short, let me put it this way: MySQL like others mentioned is just a platform while SQL is the language used in these platforms.

Hope that suffices?

Understood, thanks bro.

Raalsalghul:


What's up guys? I know it's been long since I posted here: been busy with going back to school, work and other stuff.

I remember giving the above advice the last nine months and I'll like to say that as of today, it still stands most especially from my experience working as a data analyst with an NGO while doing my MSc.

I can't emphasize it enough: learn your SQL. Again I repeat, learn your SQL if you are to switch to anything data related: whether a data analyst, scientist or engineer.

Most organizations have databases which you'll use SQL to interact with. I'm saying this because sometimes I feel there's too much emphasis on learning Python. Don't get me wrong; python is important in the world of data but it should be like number 4 on your learning list with spreadsheets and BI tools before it.

In addition to the above, I would advise you work with larger databases when practicing: the table I've been working with had about 120000 rows by 220 columns and it was just one table out of about 300 Quite large when you compare it to the ones used on your Udemy tutorial or YouTube or even Kaggle.

I'm not saying this to discourage anyone, just giving you an insider perspective. I would post more tidbits when I have the time.

If the dataset is not confidential. Please I will love you to share with me. Thanks

Omotaday:
It is not compulsory to use the discussion prompts. For self reflection, since its graded, you can just write a sentence then submit it. That is what I do. I am on the same course.

Hello,
How much in naira is the Google data analytics course per month?

Goodday all,

Please I would like someone to recommend a good and free desktop SQL software that does not require internet connection.

Internet subscription is costing me a lot of money, hence its hard to keep practicing on bigquerry.

I need to be able to download practice data sets from kaggle or any other site and work on it offline. Thank you very much for your suggestions.

Please I will also love if you share the datasets if it's not confidential to practice with and the exercise or extractions you worked on. My email is obinnaklech06@gmail.com
Thank you

Raalsalghul:


What's up guys? I know it's been long since I posted here: been busy with going back to school, work and other stuff.

I remember giving the above advice the last nine months and I'll like to say that as of today, it still stands most especially from my experience working as a data analyst with an NGO while doing my MSc.

I can't emphasize it enough: learn your SQL. Again I repeat, learn your SQL if you are to switch to anything data related: whether a data analyst, scientist or engineer.

Most organizations have databases which you'll use SQL to interact with. I'm saying this because sometimes I feel there's too much emphasis on learning Python. Don't get me wrong; python is important in the world of data but it should be like number 4 on your learning list with spreadsheets and BI tools before it.

In addition to the above, I would advise you work with larger databases when practicing: the table I've been working with had about 120000 rows by 220 columns and it was just one table out of about 300 Quite large when you compare it to the ones used on your Udemy tutorial or YouTube or even Kaggle.

I'm not saying this to discourage anyone, just giving you an insider perspective. I would post more tidbits when I have the time.

Ehido:
Goodday all,

Please I would like someone to recommend a good and free desktop SQL software that does not require internet connection.

Internet subscription is costing me a lot of money, hence its hard to keep practicing on bigquerry.

I need to be able to download practice data sets from kaggle or any other site and work on it offline. Thank you very much for your suggestions.

Why not install MYSQL or SQLSERVER MS and practice offline using dataset you get from kaggle or any other source, you can import the csv or excel file into the mysql or ssms for further practice.

Marveaux:

Hello,
How much in naira is the Google data analytics course per month?

$39 per month. It should be between 18k to 22k.

Omotaday:
$39 per month. It should be between 18k to 22k.

Woah
But on Coursera the subscription is about $14/ month or are there additional charges?

Felixitie:


Why not install MYSQL or SQLSERVER MS and practice offline using dataset you get from kaggle or any other source, you can import the csv or excel file into the mysql or ssms for further practice.

Thanks a lot for your response, I will try it out.

Raalsalghul:


Well, let me explain it like this.

SQL is the language used to communicate with databases in relational database management systems

MySQL is an example of a relational database management system same as Google Big Query, MSSQL, SQLlite, Oracle etc

In short, let me put it this way: MySQL like others mentioned is just a platform while SQL is the language used in these platforms.

Hope that suffices?

Boss, please I need your help with SQL. I sent a dm already. Thank you.

Don't use graphical user interface but command line interface when learning sql.


You can alway generate database (sql) content on Mockaroo for your practices:

https://mockaroo.com/

.

Data Analysis or Software Engineering? Which one would you advise my junior brother to choose? I need suggestions please.