Global Data Science Forum

 View Only
  • 1.  Need guidance

    Posted Mon February 03, 2020 05:47 PM

    Hey Everyone! I hope you all are doing great.

    I am absolutely new to this field and wish to have got a proper road map that is followed actually in real-time data science application. Your time and guidance will be appreciated.

    Thanking you in anticipation.

    Raffel Lawrence

  • 2.  RE: Need guidance

    Posted Tue February 04, 2020 09:18 AM
    There is a simple and free course in IBM at called Data Science Methodology ( It's short and easy.  Additionally, in Cognitive Class you can find many other introductory to mid-level courses you can use to get an introduction to the subject.  Most of them uses IBM tools such as those available on IBM Cloud, but all of them are based on open source tools such as Python, Jupyter, Anaconda, Spark and others, so, you will not be studing a proprietary IBM only tools course, but generic courses that you will be able to use anywhere.
    There are also Data Science programs sponsored by IBM, as well as many other organizations and universities in Coursera, but these are not for free. I will recommend you definitely to start with free courses available through IBM Cognitive Class.
    I hope this help.
    Daniel Lema
    GTS Information Architect & Data Scientist

    Mobile: 57-318-221-0220

  • 3.  RE: Need guidance

    Posted Wed February 05, 2020 09:14 AM

    Hello everyone. I need a guidance too and I liked the answer of Mr. Daniel Lema. I am lawyer and I am looking for opportunities at European data privacy law. I would like to know which skills I can reach and which courses I can do at IBM that can be a difference in this area. I have started to learn to code Python. Thank you.

  • 4.  RE: Need guidance

    Posted Wed February 05, 2020 03:58 AM

    Step 1. Fulfill your prerequisites

    Before you begin, you need Multivariable Calculus, Linear Algebra, and Python. If your math background is up to multivariable calculus and linear algebra, you'll have enough background to understand almost all of the probability / statistics / machine learning for the job.
    Python is the most important language for a data scientist to learn.
    R is the second most important language for a data scientist to learn. I'm saying this as someone with a statistics background and who went through undergrad mainly only using R. While R is powerful for dedicated statistical tasks, Python is more versatile as it will connect you more to production-level work.
    Step 2. Learn Probability and Statistics
    Step 3. Complete IBM's Data Science professional certificate from coursera
    Step 4. Do all of Kaggle's Getting Started and Playground Competitions

    upto this your base is strong.

    after that you can move to advance machine learning and data science courses  in coursera and handle some real world problem in kaggle

    nischal nayak

  • 5.  RE: Need guidance

    Posted Wed February 05, 2020 09:03 AM

    Hello Raffel, it is nice you are considering switching fields. 

    Nevertheless, the resources provided by other colleagues are really helpful i must admit. 
    Considering that i am not from a computer background, but i had a pretty solid background in maths and statistics. 
    The importance of maths and statistics (discrete and inferential statistics) in data science and machine learning cannot be overemphasised. 
    Note i am not giving you what i have not had to eat myself. I hope you get the saying. 
    Here are my suggestions : 
    For mathematics : 
    Mathematics for Data Science Specialization

    Mathematics for Machine Learning Specialization
    Mathematics for Machine Learning: Linear Algebra

    For statistics : 
    Coursera Data Science and Statistics.

    Introduction to Data and Statistics

    Statistics Course References

    For Data Science : 
    IBM Data Science Professional Certificate
    IBM Course on Data Science
    Introduction to Data Science in Python.

    These are just resources to start with. There are many more out there. 
    I used these ones and i am happy to share them with you. 

    Hopefully you find them usefully. 


    Damilola Omifare
    Data Scientist