BelieverDE:


So true!

I've been learning Excel for 3 months now. The truth is, Excel is so broad and I get lost in it by lingering on it. I don't know whether to move to SQL or PowerBI (as suggested from the Microsoft edx Data Analyst Xseries courses)

Gurus in the house, please suggest a learning path for me to follow

After Excel, should what should I learn next. And what course would you suggest.

@Ejiod, Kirill Eremenko's course on Machine A-Z is no longer on freetutorialsus.com


Thanks all, in anticipation of your help always.

tplayer:


Good one! Yes Excel is broad. Don't give up on it; learn it, its quite powerful and it's the go-to tool for some tasks. Many so-called data scientist or analyst don't know it and it's bad. Power BI should go next, IMHO. With just Excel and Power BI, u are already productive.

blife2:

no answer

Marveaux:

And pandas?
With the way most of you guys are emphasizing on Excel and sql, it's beginning to sound as if pandas is useless for data analysis and I've been wasting my time for the past month learning it

Marveaux:

And pandas?
With the way most of you guys are emphasizing on Excel and sql, it's beginning to sound as if pandas is useless for data analysis and I've been wasting my time for the past month learning it

tplayer:


No, it's not useless. Just start at d right place and build.

tplayer:


Just DAT people overlook Excel and it shouldnt be so.

Zabiboy:


You did not answer my question properly..
Data science is broad....You can't say you started data science in general 20 days ago....
Which tool or software did you start with?

nwele2017:

people like shinning things with big names rather than the basic. I use to be a victim of this way of reasoning but recently, I found that there is very much I can do with excel than with pandas. I spent so much learning pandas but, the little time and effort I spent learning excel made me my data analysis job very easy than I could have imagined.
pandas is very good to learn, it makes your data analysis work easy but, overlooking excel as a data analysis tool is very bad because there is much which excel can do that Pandas can not do.

blife2:


like what

nwele2017:

you are the same guy who said data science is over hyped and you still don't know the importance of Excel over pandas at least at the most basic level of data analysis!
I would have loved to enlighten you but seeing that you learnt everything about data science in two days makes me doubt if it will worth it to waste my time doing so.
learning what took people 4-6 six months to learn even with strong maths background within two days means two things: you are not being truthful to yourself or you are a genius.
if the latter is true then there is no need wasting my time teaching you what you can excel can do better than pandas at the most basic level, you can figure it out easily.
Just for the fun, I will like to see the projects you done so far

Marveaux:

Please sir, can you emphasize on "d right place and build"?
Thank you.

blife2:

how did you know well i want to know no one knows all am just saying its not as had as mastering javascipt

tplayer:

1- Excel(and relatives/natives like pivot table, power query(you can skip the M language in it), learn to create dashboards with excel(because what a lot of business people know is excel and excel is everywhere; power bi is d shiny kid getting lots of love now, and for good reasons), learn formulas and array formulas. Once u understand how cell referencing works, excel becomes easy.
1.5- power pivot (or just move to 2)
2-power bi(please learn data modelling here, please please learn how to use d dax language to create calculated columns, measures, time intelligence so you can stand out. power query and power pivot are still here too.
Note that tableau can replace power bi too. These 2 are d most popular.
3. - involve urself in d statistical aspect of what you are learning. Using tools without knowing d statistics is not complete. after all data science, forger d sexy name, is basically statistics, some pure mathematics, cimputer science, and common sense. Please read all you can about probability, distributions, Central limit theorem, experimental design, ANOVA, manova, correlation, regression, Exploratory data analysis(e.g make sure you know all about d box plot, not just how to plot it), parametric and non parametric test, post-hoc tests. etc. Baba if you try all d things here, u are already a small boss.
4- Python or R, you choice (to implement 3, and even parts of 1 and 2. They are d languages of data.

5-Now, advance statistics and calculus( For MACHINE LEARNING!!!!!! which can be implemented using python or R.) You can start machine learning by using clicks and libraries before you go under d hood. machine learning no be beans sha o and its not just simple regression. But its learnable.

6. this has no number really. insert SQL anywhere after 2.


7- PRACTICE. PRACTICE. PRACTICE!!!

If all you want is mainly extraction, cleaning, munging, visualisation of data, and creating a shiny(apologies to R guys) dashboard, A simple knowledge of statistics may do it. Excel, Power bi and SQL will do.

To become a real data scientist aka machine expert, statistics, maths, must come in.

please, I put dis together in a hurry. others here should please chime in.

Marveaux:

Wow thanks so much for this.
Finally someone has put everything in perspective and laid down a roadmap for learning.
Thanks again

tplayer:

1- Excel(and relatives/natives like pivot table, power query(you can skip the M language in it), learn to create dashboards with excel(because what a lot of business people know is excel and excel is everywhere; power bi is d shiny kid getting lots of love now, and for good reasons), learn formulas and array formulas. Once u understand how cell referencing works, excel becomes easy.
1.5- power pivot (or just move to 2)
2-power bi(please learn data modelling here, please please learn how to use d dax language to create calculated columns, measures, time intelligence so you can stand out. power query and power pivot are still here too.
Note that tableau can replace power bi too. These 2 are d most popular.
3. - involve urself in d statistical aspect of what you are learning. Using tools without knowing d statistics is not complete. after all data science, forger d sexy name, is basically statistics, some pure mathematics, cimputer science, and common sense. Please read all you can about probability, distributions, Central limit theorem, experimental design, ANOVA, manova, correlation, regression, Exploratory data analysis(e.g make sure you know all about d box plot, not just how to plot it), parametric and non parametric test, post-hoc tests. etc. Baba if you try all d things here, u are already a small boss.
4- Python or R, you choice (to implement 3, and even parts of 1 and 2. They are d languages of data.

5-Now, advance statistics and calculus( For MACHINE LEARNING!!!!!! which can be implemented using python or R.) You can start machine learning by using clicks and libraries before you go under d hood. machine learning no be beans sha o and its not just simple regression. But its learnable.

6. this has no number really. insert SQL anywhere after 2.


7- PRACTICE. PRACTICE. PRACTICE!!!

If all you want is mainly extraction, cleaning, munging, visualisation of data, and creating a shiny(apologies to R guys) dashboard, A simple knowledge of statistics may do it. Excel, Power bi and SQL will do.

To become a real data scientist aka machine expert, statistics, maths, must come in.

please, I put dis together in a hurry. others here should please chime in.

SirJerrie:
Been following this thread for about a month now(this is like my first time to comment innit though)...

So far I've been on Python... Ion know how grounded I need to be, so I'm taking my time.
Hopefully, by August I should move to Excel. Then pandas... Or Sql... Or Machine learning...

@Ejiod...Thank you very much for creating this thread... This is like a club for lovers of this career path(like myself)..
And thanks to everyone that has contributed to the growth of this thread so far...

tplayer:

1- Excel(and relatives/natives like pivot table, power query(you can skip the M language in it), learn to create dashboards with excel(because what a lot of business people know is excel and excel is everywhere; power bi is d shiny kid getting lots of love now, and for good reasons), learn formulas and array formulas. Once u understand how cell referencing works, excel becomes easy.
1.5- power pivot (or just move to 2)
2-power bi(please learn data modelling here, please please learn how to use d dax language to create calculated columns, measures, time intelligence so you can stand out. power query and power pivot are still here too.
Note that tableau can replace power bi too. These 2 are d most popular.
3. - involve urself in d statistical aspect of what you are learning. Using tools without knowing d statistics is not complete. after all data science, forger d sexy name, is basically statistics, some pure mathematics, cimputer science, and common sense. Please read all you can about probability, distributions, Central limit theorem, experimental design, ANOVA, manova, correlation, regression, Exploratory data analysis(e.g make sure you know all about d box plot, not just how to plot it), parametric and non parametric test, post-hoc tests. etc. Baba if you try all d things here, u are already a small boss.
4- Python or R, you choice (to implement 3, and even parts of 1 and 2. They are d languages of data.

5-Now, advance statistics and calculus( For MACHINE LEARNING!!!!!! which can be implemented using python or R.) You can start machine learning by using clicks and libraries before you go under d hood. machine learning no be beans sha o and its not just simple regression. But its learnable.

6. this has no number really. insert SQL anywhere after 2.


7- PRACTICE. PRACTICE. PRACTICE!!!

If all you want is mainly extraction, cleaning, munging, visualisation of data, and creating a shiny(apologies to R guys) dashboard, A simple knowledge of statistics may do it. Excel, Power bi and SQL will do.

To become a real data scientist aka machine expert, statistics, maths, must come in.

please, I put dis together in a hurry. others here should please chime in.

iCode2:
So much to learn in this data science/analysis thingy!! And it seems one will need to learn almost everything before being able to land a job with it.

Ejiod:

Reason is that most businesses and corporate organisation store their data on database and they look for who will pull that data up.
Pandas is great but thats descriptive data analysis which many software these days can do.The advantage you have with pandas is data wrangling.

Zabiboy:


That's because you are learning to get a job
I know we all want to get employed but instead of learning to get a job, learn to improve yourself....if you are thoroughly good with excel, Tableau/powerbi ( one of them ) and even a small knowledge of sql, you are already fit for jobs...Then if you get one or while submitting letters, you can continue expanding....

nwele2017:

Who will pay you for just knowing tools without using it to gain insight. You definitely need statistics for you to be able to use these tools to gain insight effectively.
For example, Somebody who doesn't know the difference between Categorical and numerical variables cannot use tabulea or powerbi effectively, he or she will never know the perfect graphical representation to gain insight from this variables.
Statistics is definitely the number one thing anybody who wants to be a data scientist/analyst, businesses intelligence analyst,data miner... needs know because everything about those job mentioned above is all about finding patterns, gaining insight, predicting the future and communicating the result of the data for effective decision to be made.
Nobody, will ever employee you to come and just give graphical representation which you don't even understand. Knowing the the tools is just like 40% of the skills needed, you need understanding of statistics, understanding of data in its context and effective communication skills for you to be able to make up to 100%
So add statistics among what you listed

SOLARPOWER1:


Which of the SQL is preferable Mysql or MS SERVER .....I have done about three courses in Mysql and I am now very comfortable with queries... But I saw a lengthy course on sql using MS Server and how to use it in reporting ....Should I take this MS SERVER course or just focus more on Mysql...I don't want to be learning many things that are not in sequence as this might get me confuse ....I need advice here

BelieverDE:


So true!

I've been learning Excel for 3 months now. The truth is, Excel is so broad and I get lost in it by lingering on it. I don't know whether to move to SQL or PowerBI (as suggested from the Microsoft edx Data Analyst Xseries courses)

Gurus in the house, please suggest a learning path for me to follow

After Excel, should what should I learn next. And what course would you suggest.

@Ejiod, Kirill Eremenko's course on Machine A-Z is no longer on freetutorialsus.com


Thanks all, in anticipation of your help always.

funimages:


I have read through your chronicles, I perceive that you are a man that carry grace, I like to come under and tap from your grace. My whatapp number is 09099195753. If you give me yours, I will call or chat you up immediately. Thanks.

Zabiboy:


That's because you are learning to get a job
I know we all want to get employed but instead of learning to get a job, learn to improve yourself....if you are thoroughly good with excel, Tableau/powerbi ( one of them ) and even a small knowledge of sql, you are already fit for jobs...Then if you get one or while submitting letters, you can continue expanding....

nwele2017:

people like shinning things with big names rather than the basic. I use to be a victim of this way of reasoning but recently, I found that there is very much I can do with excel than with pandas. I spent so much learning pandas but, the little time and effort I spent learning excel made me my data analysis job very easy than I could have imagined.
pandas is very good to learn, it makes your data analysis work easy but, overlooking excel as a data analysis tool is very bad because there is much which excel can do that Pandas can not do.

lymelyte:
please where can I get a good full video tutorial on excel. I haven't found any concrete tool on this..

SavageBoy:
@Ejiod good afternoon,how're you doing sir?

Please I just started learning HTML&CSS using freecodecamp YouTube tutorial videos, from the comment section on their YouTube channel it seems like they tutorial video for HTML&CSS is really good so I downloaded it.It's about 11hours+(Thanks to my 3airtel sim cards)

But the issue now is that I'm finding it a bit difficult to comprend what the tutor is teaching and he is a bit fast.The tutor sound like an Indian, maybe that's the reason

But before downloading this tutorial video I was watching Bucky Robert(newboston) videos and the guy seem to be very good and understandable but I had to stop because a programmer friend or mine said his videos are outdated and lot of stuffs have changed in the HTML,CSS and JavaScript world so I had to stop.

Meanwhile he said Visual code text editor is better than Notepad++ which is what the newboston guy uses.
So I'm just asking if the newboston guy tutorial videos are really outdated or maybe I could still use it