PowerBi is a more professional and analytical tool than excel, though very similar. One may consider PowerBi as excel that has wings.
Since you are good at using excel already, PowerBi won't pose much problems to you. Adding PBi skills to your portfolio will only broaden your expertise.

AgentPein:

sir, is it a software or language? and is it something i will have to get tutorial on? if Yes where can i get them sir?
thanks in advance

IceColdVeins:
PowerBi is a more professional and analytical tool than excel, though very similar. One may consider PowerBi as excel that has wings.
Since you are good at using excel already, PowerBi won't pose much problems to you. Adding PBi skills to your portfolio will only broaden your expertise.

Thanks boss, I will download it and update you

This data science journey is taking too long I must confess.

If I had focused on software dev, I'd have covered the full .Net core by now - including entity, testing and everything that concerns web dev

Having consumed Soo much for the past 4months, i still have some gaps to be filled - which will eventually lead to software dev!

May God help us!

Who's experiencing same?

Also, who got an invite to Xyples LLC for the on-site assessment for data analyst role scheduled for today?

Imakeherdrip:
This data science journey is taking too long I must confess.

If I had focused on software dev, I'd have covered the full .Net core by now - including entity, testing and everything that concerns web dev

Having consumed Soo much for the past 4months, i still have some gaps to be filled - which will eventually lead to software dev!

May God help us!

Who's experiencing same?

Also, who got an invite to Xyples LLC for the on-site assessment for data analyst role scheduled for today?

Same here.. You aren't alone. I had to drop data science and focus on analysis part. Power BI and excel + Python. Still taking time although other commitments are slowing me. Its well.

Hinokami:


Same here.. You aren't alone. I had to drop data science and focus on analysis part. Power BI and excel + Python. Still taking time although other commitments are slowing me. Its well.

Good

I think the days of getting a job as a data analyst by simply learning only SQL, python and Excel is drawing to a close(I might be wrong).
Recruiters are becoming inhumane these days.

I applied for a data scientist (and software dev) job. I was given a task to create a movie recommender to recommend movies to people, which I did with the help of google. Only for the hr to send me a second task to build a CRUD app using express, mongo, react, typescript
With testing using mocha, jest , etc

I started but was discouraged (it means I'll have to go back to relearn node and web testing. And I need to learn react as I only have experience using vuejs) and I'm currently learning asp as I speak. I had to ignore the project before I Die of stress!

Back to data science
Someone asked me to build my portfolio with the following projects since I do not have any industrial experience.

Machine learning projects
1. CNN
2. RNN
3. NLP

Descriptive Analysis
1. Create dashboards showing various Analysis
2. Make sure to use scrapy for data sourcing

Subscribe (monthly) for a cloud service to deploy your models (costs money)

Build a Flask wrapper(website) around your ML model for people to use.

The above would take some months to achieve (especially if you have a job).


And I'm yet to learn scrapy --

Thank you Lord!

Imakeherdrip:



Good

Someone asked me to build my portfolio with the following projects since I do not have any industrial experience.

Machine learning projects
1. CNN
2. RNN
3. NLP

Descriptive Analysis
1. Create dashboards showing various Analysis
2. Make sure to use scrapy for data sourcing

Subscribe (monthly) for a cloud service to deploy your models (costs money)

The above would take some months to achieve (especially if you have a job).


And I'm yet to learn scrapy --

Thank you Lord!

Wow.. That's quite lot. Slow but steady.. Surely we'd get there.

Imakeherdrip:



Good

I think the days of getting a job as a data analyst by simply learning only SQL, python and Excel is drawing to a close(I might be wrong).
Recruiters are becoming inhumane these days.

I applied for a data scientist (and software dev) job. I was given a task to create a movie recommender to recommend movies to people, which I did with the help of google. Only for the hr to send me a second task to build a CRUD app using express, mongo, react, typescript
With testing using mocha, jest , etc

I started but was discouraged (it means I'll have to go back to relearn node and web testing. And I need to learn react as I only have experience using vuejs) and I'm currently learning asp as I speak. I had to ignore the project before I Die of stress!

Back to data science
Someone asked me to build my portfolio with the following projects since I do not have any industrial experience.

Machine learning projects
1. CNN
2. RNN
3. NLP

Descriptive Analysis
1. Create dashboards showing various Analysis
2. Make sure to use scrapy for data sourcing

Subscribe (monthly) for a cloud service to deploy your models (costs money)

Build a Flask wrapper(website) around your ML model for people to use.

The above would take some months to achieve (especially if you have a job).


And I'm yet to learn scrapy --

Thank you Lord!

Slow and steady wins the race. Thanks for sharing!

Imakeherdrip:



Good

I think the days of getting a job as a data analyst by simply learning only SQL, python and Excel is drawing to a close(I might be wrong).
Recruiters are becoming inhumane these days.

I applied for a data scientist (and software dev) job. I was given a task to create a movie recommender to recommend movies to people, which I did with the help of google. Only for the hr to send me a second task to build a CRUD app using express, mongo, react, typescript
With testing using mocha, jest , etc

I started but was discouraged (it means I'll have to go back to relearn node and web testing. And I need to learn react as I only have experience using vuejs) and I'm currently learning asp as I speak. I had to ignore the project before I Die of stress!

Back to data science
Someone asked me to build my portfolio with the following projects since I do not have any industrial experience.

Machine learning projects
1. CNN
2. RNN
3. NLP

Descriptive Analysis
1. Create dashboards showing various Analysis
2. Make sure to use scrapy for data sourcing

Subscribe (monthly) for a cloud service to deploy your models (costs money)

Build a Flask wrapper(website) around your ML model for people to use.

The above would take some months to achieve (especially if you have a job).


And I'm yet to learn scrapy --

Thank you Lord!

LEARN EVERY-DAMN-THING MODE ACTIVATED .

WITH ALOT OF VEXATION ... NO REMORSE !!

This thread is �. I started my journey as a Data Scientist last three months. I’ve learnt SQL. Learnt pandas. Numpy. Matplotlib Seaborn and now I’m learning Machine learning. Please I’m I making progress.

Hinokami:


Same here.. You aren't alone. I had to drop data science and focus on analysis part. Power BI and excel + Python. Still taking time although other commitments are slowing me. Its well.

I thought I was the only one experiencing such.

Singingbae:
This thread is �. I started my journey as a Data Scientist last three months. I’ve learnt SQL. Learnt pandas. Numpy. Matplotlib Seaborn and now I’m learning Machine learning. Please I’m I making progress.

Oui

God speed!

Singingbae:
This thread is �. I started my journey as a Data Scientist last three months. I’ve learnt SQL. Learnt pandas. Numpy. Matplotlib Seaborn and now I’m learning Machine learning. Please I’m I making progress.

The effrontery!


Not trying to scare you, what happened is that you've become familiar with those mentioned languages and libraries, introduced to basic syntax but you haven't learnt anything, nothing.

HewlettPackard:


The effrontery!


Not trying to scare you, what happened is that you've become familiar with those mentioned languages and libraries, introduced to basic syntax but you haven't learnt anything, nothing.

Man you scared me. I’ve actually gone far in the regression stuff. I know the libraries. The sklearn and statsmodel and all but I can’t say yet I’m good in it. But machine learning is fun tho �

Singingbae:
This thread is �. I started my journey as a Data Scientist last three months. I’ve learnt SQL. Learnt pandas. Numpy. Matplotlib Seaborn and now I’m learning Machine learning. Please I’m I making progress.

Of course you're making good progress keep it up.

HewlettPackard:


The effrontery!


Not trying to scare you, what happened is that you've become familiar with those mentioned languages and libraries, introduced to basic syntax but you haven't learnt anything, nothing.

Sad truth!

But he is making progress - we can not say he isn't

Having completed machine learning courses on udemy I still found myself lost on kaggle projects.

I had to start reading other people's notebook to really get a hang of various data preprocessing and error estimation techniques.

Things like model grading using rmse, log-loss, etc

Mehn, the list is endless my brother...but we are moving!

Merci

Singingbae:
Man you scared me. I’ve actually gone far in the regression stuff. I know the libraries. The sklearn and statsmodel and all but I can’t say yet I’m good in it. But machine learning is fun tho �

Ça c'est perfait!

Singingbae:
Man you scared me. I’ve actually gone far in the regression stuff. I know the libraries. The sklearn and statsmodel and all but I can’t say yet I’m good in it. But machine learning is fun tho �

quality over quantity, always put that in mind.

Imakeherdrip:


Sad truth!

But he is making progress - we can not say he isn't

Having completed machine learning courses on udemy I still found myself lost on kaggle projects.

I had to start reading other people's notebook to really get a hang of various data preprocessing and error estimation techniques.

Things like model grading using rmse, log-loss, etc

Mehn, the list is endless my brother...but we are moving!

Merci

I've told myself I can't be the expert I really want to be by watching videos, they are great resources of learning, agreed, but it's never enough.

Read books!

I'd take one good book over a 100 videos any day.

I remember when I started will SQL, after watching different videos tutorial, I felt like a king, thought I've known everything about the field, talking like that OP
My naivety wasn't glaring until I picked up a book on it, I couldn't read past chapter 2, closed it, picked up another, went back to the previous, the cycle continues.

Imagine the time these processes takes, for various fields of study, and I still can't say to anyone that I've learnt SQL, because I know that, what I know is not up to 20% of what is covered in the field.

You took 1,2,3 udemy data science course, completed them and you think you are now a data scientist? bro your journey just started.

HewlettPackard:



I've told myself I can't be the expert I really want to be by watching videos, they are great resources of learning, agreed, but it's never enough.

Read books!

I'd take one good book over a 100 videos any day.

I remember when I started will SQL, after watching different videos tutorial, I felt like a king, thought I've known everything about the field, talking like that OP
My naivety wasn't glaring until I picked up a book on it, I couldn't read past chapter 2, closed it, picked up another, went back to the previous, the cycle continues.

Imagine the time these processes takes, for various fields of study, and I still can't say to anyone that I've learnt SQL, because I know that, what I know is not up to 20% of what is covered in the field.

You took 1,2,3 udemy data science course, completed them and you think you are now a data scientist? bro your journey just started.

well, if this is the case that means no one would be ripe for a job then, maybe you don't know that developers who built those programs we use are still consulting for help when they get stuck at times, even the best of the best with years of experience still log on to stackoverflow for help....
my point is, one can't "graduate" from programming school, just keep building on... and the best way to get better is to get a job and handle real world project on a daily basis, books are great, but videos are also enough to get an entry level job.

HewlettPackard:



I've told myself I can't be the expert I really want to be by watching videos, they are great resources of learning, agreed, but it's never enough.

Read books!

I'd take one good book over a 100 videos any day.

I remember when I started will SQL, after watching different videos tutorial, I felt like a king, thought I've known everything about the field, talking like that OP
My naivety wasn't glaring until I picked up a book on it, I couldn't read past chapter 2, closed it, picked up another, went back to the previous, the cycle continues.

Imagine the time these processes takes, for various fields of study, and I still can't say to anyone that I've learnt SQL, because I know that, what I know is not up to 20% of what is covered in the field.

You took 1,2,3 udemy data science course, completed them and you think you are now a data scientist? bro your journey just started.

Chill bro, no need for this. We are only trying to be better at a time.

Some persons here are already getting frustrated - don't add to their agony

I have tonnes of books but I barely open them these days because what I need for the job I already have in videos.

Do you know why I once hated SQL and web design?

Boooks!!!!! - outdated books!!!!!

They made my life extremely difficult -- not because I wasn't smart enough, but because they were outdated(considering how rapid the tech space is) with lots of theory that you may never apply.

And reading books takes a lot of mental resources!

I just found out how interesting software development is and I'm really loving it, after many years of ignorance (you can check out my moniker to see when I started web dev).

My point is, you don't have to know everything to start applying for a job.

For a data science position, we already know what to do to get a job - Ejiod already told us...

If all a company needs is someone to create data pipelines for different data sources to various destinations why would it matter if you know python? They don't care! Just get the job at hand done.

Do you know how sad it is to tell someone who has been studying for months that he hasn't even started , when infact he already has the skill set to pick up a junior role

Peace

Dahyormine:
well, if this is the case that means no one would be ripe for a job then, maybe you don't know that developers who built those programs we use are still consulting for help when they get stuck at times, even the best of the best with years of experience still log on to stackoverflow for help....
my point is, one can't "graduate" from programming school, just keep building on... and the best way to get better is to get a job and handle real world project on a daily basis, books are great, but videos are also enough to get an entry level job.

Well, different persons with different reasons for programming. Personally landing a job is not my end game, it's much more and bigger maybe that's why approaches are different.

wisemania:



Chill bro, no need for this. We are only trying to be better at a time.

Some persons here are already getting frustrated - don't add to their agony

I have tonnes of books but I barely open them these days because what I need for the job I already have in videos.

Do you know why I once hated SQL and web design?

Boooks!!!!! - outdated books!!!!!

They made my life extremely difficult -- not because I wasn't smart enough, but because they were outdated(considering how rapid the tech space is) with lots of theory that you may never apply.

And reading books takes a lot of mental resources!

I just found out how interesting software development is and I'm really loving it, after many years of ignorance (you can check out my moniker to see when I started web dev).

My point is, you don't have to know everything to start applying for a job.

For a data science position, we already know what to do to get a job - Ejiod already told us...

If all a company needs is someone to create data pipelines for different data sources to various destinations why would it matter if you know python? They don't care! Just get the job at hand done.

Do you know how sad it is to tell someone who has been studying for months that he hasn't even started , when infact he already has the skill set to pick up a junior role

Peace

What I see here is that you don't like truth, you want someone that will tell you programming is easy, if it was everyone would be doing it.

You don't have the mental prowess for reading and you want to programme, you are just kidding yourself.

Peace bro.

HewlettPackard:



What I see here is that you don't like truth, you want someone that will tell you programming is easy, if it was everyone would be doing it.

You don't have the mental prowess for reading and you want to programme, you are just kidding yourself.

Peace bro.

I look for SMARTER and FASTER approach to learning. Books, videos or even audio. What matter is SPEED of assimilation. RETENTION ONLY come when u continue to practice what you learnt or assimilated in the first place.

I only read books mostly when I am ready to go to bed cos I know 30minutes max I must doze off. But I still learned something. I use videos for ACTIVE LEARNING . And I increase the speed of playback sometimes when I am in HYPER-LEARNING mode.

I have programmed my life in such a way that the only time I am not learning is when am sleeping. 90% of my waking state its either I am WATCHING somethin, READING something or LISTENING to something. HARDLY ANY GAP.

The most important things to note:
(1) don't stop to learning, and
(2) constant application of what you have learnt.

The irony of this matter is the deeper you go in this data science field the easier new concepts become.

GOD PUNISH EXCUSE !!!

wellsaid:


I look for SMARTER and FASTER approach to learning. Books, videos or even audio. What matter is SPEED of assimilation. RETENTION ONLY come when u continue to practice what you learnt or assimilated in the first place.

I only read books mostly when I am ready to go to bed cos I know 30minutes max I must doze off. But I still learned something. I use videos for ACTIVE LEARNING . And I increase the speed of playback sometimes when I am in HYPER-LEARNING mode.

I have programmed my life in such a way that the only time I am not learning is when am sleeping. 90% of my waking state its either I am WATCHING somethin, READING something or LISTENING to something. HARDLY ANY GAP.

The most important things to note:
(1) don't stop to learning, and
(2) constant application of what you have learnt.

The irony of this matter is the deeper you go in this data science field the easier new concepts become.

GOD PUNISH EXCUSE !!!

I understand you bro, I'm not totally disregarding video tutorials, my stance is that they don't provide in-depth explanations like texts do. SQL for example, I watched various videos on E-R diagrams rules and Normalization, I swear none of those videos thought me 10% of what a text on those topics did.

My point, if you are want to be like every Joe on the block, you can avoid texts, but man if you are want to be that something extra, well...

All in all, like the old saying goes "practice makes perfect", watch all the videos, read a damn library if you don't practice on them, again well...

Peace bro.

HewlettPackard:


I understand you bro, I'm not totally disregarding video tutorials, my stance is that they don't provide in-depth explanations like texts do. SQL for example, I watched various videos on E-R diagrams rules and Normalization, I swear none of those videos thought me 10% of what a text on those topics did.

My point, if you are want to be like every Joe on the block, you can avoid texts, but man if you are want to be that something extra, well...

All in all, like the old saying goes "practice makes perfect", watch all the videos, read a damn library if you don't practice on them, again well...

Peace bro.

Agreed.. Actually a lot of information to solve many non-trivial problems are found in documentations, academic and research papers.

Good evening, boss. I just stumbled on your thread this evening and it really helped a lot. I've been thinking on which one to go for between database Management and software development. I already learnt CSS and HTML. I'm still a student and a kid. Just got admission into a university this year. Boss, can I start learning database Management now or I should wait for a while

HewlettPackard:


quality over quantity, always put that in mind.

Bruh. Trust me I’m dedicating enough time and I’m challenged by this thread. Thanks for this advise

HewlettPackard:

I've told myself I can't be the expert I really want to be by watching videos, they are great resources of learning, agreed, but it's never enough.

Read books!

I'd take one good book over a 100 videos any day.

I remember when I started will SQL, after watching different videos tutorial, I felt like a king, thought I've known everything about the field, talking like that OP
My naivety wasn't glaring until I picked up a book on it, I couldn't read past chapter 2, closed it, picked up another, went back to the previous, the cycle continues.

Imagine the time these processes takes, for various fields of study, and I still can't say to anyone that I've learnt SQL, because I know that, what I know is not up to 20% of what is covered in the field.

You took 1,2,3 udemy data science course, completed them and you think you are now a data scientist? bro your journey just started.

I beg to differ. People acquire knowledge in different ways either in books, video tutorials or both. It's all about identifying the best method that suits you. I learnt the basics of Python from YouTube and not from books.

A good practically oriented video tutorial is more than enough to get one started in building projects. If you intend knowing all and all about data science by reading books upon books, 10 years from now you'll be amazed to see how much you still need to know cos it's an endless journey.

Quote me anywhere there's no professional programmer that has all it takes and codes without looking up solutions to errors.

The most important thing about data science and programming in general is your projects and portfolios not how much you know cos even those at google knows they're still learning.

Abcruz:


I beg to differ. People acquire knowledge in different ways either in books, video tutorials or both. It's all about identifying the best method that suits you. I learnt the basics of Python from YouTube and not from books.

A good practically oriented video tutorial is more than enough to get one started in building projects. If you intend knowing all and all about data science by reading books upon books, 10 years from now you'll be amazed to see how much you still need to know cos it's an endless journey.

Quote me anywhere there's no professional programmer that has all it takes and codes without looking up solutions to errors.

The most important thing about data science and programming in general is your projects and portfolios not how much you know cos even those at google knows they're still learning.

He's actually saying nothing but the truth. Plain truth. Videos only give a false sense of understanding and you think you are making progress. Following video tutorials to replicate what the tutor is doing is not the same as building solid projects. If you really want to master a concept in data science (or any field), read books, docs, research paper and combine them with videos, people's codes, medium articles etc.

Well, as someone rightly pointed out, we are into DA for different reasons. Some need job, some just do it for fun while some people are using it for research. Whatever method you use to study, as long as it works for you then you are good to go. However, no one can go deep in any concept by just watching videos.

As far as I'm concerned, I study using multiple sources and resources and that works well for me.

ibromodzi:


He's actually saying nothing but the truth. Plain truth. Videos only give a false sense of understanding and you think you are making progress. Following video tutorials to replicate what the tutor is doing is not the same as building solid projects. If you really want to master a concept in data science (or any field), read books, docs, research paper and combine them with videos, people's codes, medium articles etc.

Well, as someone rightly pointed out, we are into DA for different reasons. Some need job, some just do it for fun while some people are using it for research. Whatever method you use to study, as long as it works for you then you are good to go. However, no one can go deep in any concept by just watching videos.

As far as I'm concerned, I study using multiple sources and resources and that works well for me.

Videos will only give you a false sense of understanding if you're only watching and not practicing. Besides if you should use books to learn are you not also replicating what the author has written? Will you also call that a false sense of progress?

Yes it is good to learn with different means but inferring that those who take udemy courses to learn haven't started is farfetched cos even the book doesn't teach you all there is to know.

You just nailed it. That my point exactly. People learn and comprehend in different ways. Saying watching videos is not enough to become grounded is totally off the point. I learnt everything I know in Data Science through videos and online Bootcamp. I'm still a work in progress though, Nobody knows it all. But I can tell you for free that I have learnt enough to land me an entry-level data science role. I got a couple of invites for interview for data science jobs in the USA, I couldn't attend because they all want candidates residing in the US even though its remote. The idea was to convert remote workers to full-time after covid subsides.

I just want to enjoin everyone striving hard to learn data science not to give up. There a long road ahead, but appreciate yourself for what you have learnt so far. It is not easy to learn excel alone to mastery level not to talk of SQL and Machine Learning that requires a lot of complex algorithm for building your models. Have a plan, draw a learning schedule for your self and give yourself timelines. Don't try to learn everything at once. Take it one step at a time.

What seems difficult today, will seem like a stroll in the park to you in a couple of months from now with hard work, consistency and dedication. Download different data sets on Kaggle and try to make meaning out of them using what you have learnt so far, be it excel, PowerBI, SQL, TABLEAU or Machine learning.

Believe me, you have what it takes to become a full-fledged data scientist.

Don't be discouraged guys. We will all come back here one day to share our story of how we landed a great job through our skills.

KEEP GRINGING.

Abcruz:


I beg to differ. People acquire knowledge in different ways either in books, video tutorials or both. It's all about identifying the best method that suits you. I learnt the basics of Python from YouTube and not from books.

A good practically oriented video tutorial is more than enough to get one started in building projects. If you intend to know all and all about data science by reading books upon books, 10 years from now you'll be amazed to see how much you still need to know cos it's an endless journey.

Quote me anywhere there's no professional programmer that has all it takes and codes without looking up solutions to errors.

The most important thing about data science and programming in general is your projects and portfolios not how much you know cos even those at google knows they're still learning.