How Can You Learn Data Science on self-paced method yourself?

i recently took interest in data analysis in excel and python and the learning has been top notch. i would crave to assist with “the method” i feel is most great for absolute starters and intermediate learners.

The question is “How do I learn data analysis with python”.

I would answer this by outlying a few methods that have helped tremendously.

Commit your time to it. You can’t learn by just reading blogs. you simply need to practice and as such would need a laptop or at best a desktop computer. there is self-deceit in wanting to learn with your phone. Truth is everyone starts somewhere. The best way to learn is by practice. trying to reproduce what has been done with a good and clearer understanding.
Learn Python Fundamentals: This is the basic requirement should you want data to obey and respond to your commands. One tool that came in handy for me was jupyter notebook and spyder. while i prefer jupyter owing to its ease of use, you can download the entire tools by installing anaconda. it comes pre-loaded with pycharm, jupyter notebook, spyder and R just to mention a few. As you learn the fundamentals, try to join local meet up groups, Kaggle community(create a Kaggle account for free).
Practice Python Projects: You only learn when you unlearn to learn. where you have projects done by others, you can re-produce same to your goal so you know how to avoid errors. when learning, it is common practice to make errors. you can make simple errors that can take hours and days to fanthom. that is where practice and practice comes to play.
Learn Python data science libraries: Once you get a goal at Python, it becomes expedient to learn the libraries as these are codes already written by people that you can easily call and use in your own code instead of writing from start. The three best and most important Python libraries for data science are NumPy, Pandas, and Matplotlib.
Numpy: A library that allows you to work on mathematical and statistical operations easily.

Pandas: A library that allows you to resolve data in table format easily. With pandas, you can fetch your data in rows and columns and allows you to explore and play with your data.

Matplotlib: All the data you worked on in Numpy and Pandas can easily be viewed in charts that can easily be interpreted. with these charts, you can make inference from your data.

5. Build a datascience portfolio as you learn:

The essence of datascience or analysis is to make inference from your data such that you can talk to it and it can convey information to you.

The process starts from data cleaning and data pre-processing to makingeasy to read visualizations. Having great-looking charts in a project will make your portfolio stand out.

Displaying projects like these (done by you) gives fellow data scientists an opportunity to potentially collaborate with you, and shows future employers that you’ve truly taken the time to learn Python and other important programming skills.

One of the nice things about data science is that your portfolio doubles as a resume while highlighting the skills you’ve learned, like Python programming.

6. Apply Techniques learnt to sharpen your skills

Learning is the constant thing. Should you want to be comfortable with regression, classification, and k-means clustering models. You can also step into machine learning – bootstrapping models and creating neural networks using scikit-learn.

At this point, programming projects can include creating models using live data feeds that gives you comfort. Machine learning models of this kind adjust their predictions over time.

7. What Resources can you employ.

My whole journey commenced about 3 months ago and i would not mince words at the resources i have used to get this far. it has been an interesting journey into data science and i feel just anyone no matter the level can get started to and achive just much.

I have used EDUCBA as a great resource tool.

eduCBA is an online training provider which provides multiple ranging of courses or you can call it as online training programs to learners, professionals, readers, candidates/students & many more who wish to learn something new & wish to gain practical knowledge i.e. implications of theoretical knowledge into the corporate life.

It is simply Asia’s largest online learning platform with over 5000+ courses taught by real life professionals.

What is there to learn:

Well tailored pattern to grow your career in data analysis
Plethora of online training courses at one place
Lifetime Subscription Facility
Learn to analyze & interpret concepts and situations like industry experts
Live case scenarios & exposure to corporate world trainings
Provides Certificate on the successful completion of the course
Technical Support & Guidance from the educba team
Below is a snapshot of my dashboard. what insterest me most are the real life projects contained which are applicable to let you get the best from learning.

I am currently machine learning and AI

I recently began a study group for Nigerian AI enthusiasts. The group is still quite new and I'm looking for other like minds to join and brainstorm with each other. If it interests you, you can join on Discord using this link. https://discord./fkdBEjae

nasuite:
How Can You Learn Data Science on self-paced method yourself?

i recently took interest in data analysis in excel and python and the learning has been top notch. i would crave to assist with “the method” i feel is most great for absolute starters and intermediate learners.

The question is “How do I learn data analysis with python”.

I would answer this by outlying a few methods that have helped tremendously.

Commit your time to it. You can’t learn by just reading blogs. you simply need to practice and as such would need a laptop or at best a desktop computer. there is self-deceit in wanting to learn with your phone. Truth is everyone starts somewhere. The best way to learn is by practice. trying to reproduce what has been done with a good and clearer understanding.
Learn Python Fundamentals: This is the basic requirement should you want data to obey and respond to your commands. One tool that came in handy for me was jupyter notebook and spyder. while i prefer jupyter owing to its ease of use, you can download the entire tools by installing anaconda. it comes pre-loaded with pycharm, jupyter notebook, spyder and R just to mention a few. As you learn the fundamentals, try to join local meet up groups, Kaggle community(create a Kaggle account for free).
Practice Python Projects: You only learn when you unlearn to learn. where you have projects done by others, you can re-produce same to your goal so you know how to avoid errors. when learning, it is common practice to make errors. you can make simple errors that can take hours and days to fanthom. that is where practice and practice comes to play.
Learn Python data science libraries: Once you get a goal at Python, it becomes expedient to learn the libraries as these are codes already written by people that you can easily call and use in your own code instead of writing from start. The three best and most important Python libraries for data science are NumPy, Pandas, and Matplotlib.
Numpy: A library that allows you to work on mathematical and statistical operations easily.

Pandas: A library that allows you to resolve data in table format easily. With pandas, you can fetch your data in rows and columns and allows you to explore and play with your data.

Matplotlib: All the data you worked on in Numpy and Pandas can easily be viewed in charts that can easily be interpreted. with these charts, you can make inference from your data.

5. Build a datascience portfolio as you learn:

The essence of datascience or analysis is to make inference from your data such that you can talk to it and it can convey information to you.

The process starts from data cleaning and data pre-processing to makingeasy to read visualizations. Having great-looking charts in a project will make your portfolio stand out.

Displaying projects like these (done by you) gives fellow data scientists an opportunity to potentially collaborate with you, and shows future employers that you’ve truly taken the time to learn Python and other important programming skills.

One of the nice things about data science is that your portfolio doubles as a resume while highlighting the skills you’ve learned, like Python programming.

6. Apply Techniques learnt to sharpen your skills

Learning is the constant thing. Should you want to be comfortable with regression, classification, and k-means clustering models. You can also step into machine learning – bootstrapping models and creating neural networks using scikit-learn.

At this point, programming projects can include creating models using live data feeds that gives you comfort. Machine learning models of this kind adjust their predictions over time.

7. What Resources can you employ.

My whole journey commenced about 3 months ago and i would not mince words at the resources i have used to get this far. it has been an interesting journey into data science and i feel just anyone no matter the level can get started to and achive just much.

I have used EDUCBA as a great resource tool.

eduCBA is an online training provider which provides multiple ranging of courses or you can call it as online training programs to learners, professionals, readers, candidates/students & many more who wish to learn something new & wish to gain practical knowledge i.e. implications of theoretical knowledge into the corporate life.

It is simply Asia’s largest online learning platform with over 5000+ courses taught by real life professionals.

What is there to learn:

Well tailored pattern to grow your career in data analysis
Plethora of online training courses at one place
Lifetime Subscription Facility
Learn to analyze & interpret concepts and situations like industry experts
Live case scenarios & exposure to corporate world trainings
Provides Certificate on the successful completion of the course
Technical Support & Guidance from the educba team
Below is a snapshot of my dashboard. what insterest me most are the real life projects contained which are applicable to let you get the best from learning.

Boss pls I just started my journey on data science, am currently learning excel pls after this what next. Can I substitute python for sql

where are you based?

Am interested in Data Science... pls where do I start from?

You can get the resource materials...

Chat 0809 600 2981

i want to start learning data analysis. What type of laptop can i buy? i am on a budget.

Delightful8:
i want to start learning data analysis. What type of laptop can i buy? i am on a budget.

I have a Dell Inspirion laptop for sale

kobakoko:


I have a Dell Inspirion laptop for sale

How much?

BlackSan:


How much?

150k—negotiable
DM on 09070990976 for further details. I’m not really conversant with Nairaland

BlackSan:


How much?

150k negotiable

Location Unilag, Lagos

Original receipt from DELL Available
09070990976