Data science course roadmap?

A Data Science training syllabus is present on the internet which probably looks easy but to understand the concept, one needs to master many concepts/steps involved which need to be followed without fail as a ritual. The concept of a Mind map for Data Science has been introduced by 360DigiTMG to help one understand the concepts in a nutshell.

Data science Mindmaps?

We at 360DigiTMG first use this to make the participants understand as a data science course mind map and then make them understand how this helps things work easily as they start their Data Science journey. We at 360DigiTMG strive to help the participants master not just the concepts but also follow every step needed in real time with the help of Data science Mindmaps. We emphasize and get the concepts revised daily and make one consider these Mind maps for Data Science as the Bible which will not just help one with the training but also helped many crack the interviews as they put no effort into responding to the interviewer in the required order of the work steps.

This was introduced as a data science course roadmap to help the participants just understand the agenda flow then as we started working on this further we enhanced this Data science Mindmaps to a level that can help encapsulate the concept of Data Science. The summarized format of the entire data science course syllabus is a one-pager which by just double-clicking on the concept expands to just give a one-liner about the topic and can be expanded to get examples wherever needed.

One analyzes how these Data science Mindmaps help them pave their path in this field. Our team had taken the feedback from the participants on how this Data science Mindmaps made the change in analyzing and memorizing the concept while learning and working.

Stepwise learning of Data Science

Here to start with what gets to understand from the first glance of the data science mindmap. The concept of the Project Management methodology is called CRISP ML(Q), which stands for Cross Industry Standard Process for Machine Learning with Quality Assurance.

The first thing that comes to one’s mind is why one needs the concept of Project Management in the space of Data Science. Well, when we at 360DigiTMG make a Data Scientist we are not pushing our participants into the herd of unemployed or some experienced person just doing the course as this is one of the most looked for courses but we want them to stand unique with the possible implementation as and when needed in their project. We are getting them industry ready so that they stand above all regarding the skillset they carry. The phases of Project Management are explained so deeply and clearly that from day 1, they will understand the importance of how these concepts work in creating a perfect cakewalk when one starts to perform on the projects.

They start looking at the problem statement or the Business problem with just not any random issue that the client comes with but try to analyze what needs to be addressed and prioritize things which helps them design a working model which will never fail. It is making the working a fool-proof approach so things start falling into alignment as they proceed every step.

One can now move to the next step of Data Understanding. We just knew the alphabet and numbers and later got introduced to special characters but one gets to the concepts from the basics of what this data is and how is it classified. Everything that was learned in school as the number system further evolved in understanding how numbers can be differently looked at. If numbers show up as height, weight, or monetary then we call it Ratio data, and if the same numbers show up as temperature then we classify them under intervals, these numbers now come in order then we say count data.

When this kind of understanding was given, then participants could correlate everything that they knew but didn’t analyze it before and now they understand that it can work so differently.

Data Science Mindmaps help one recollect the concepts that we learned in school days which are like a simple line equation to the easiest of the concept called probability. Most of the things that we use as Data Scientists are the concepts learned in as low as grade 6. While these are clear then we move to Data preparation again with the known topic of Mean, Median, etc. Interpreting and creating the histograms during the school days was one the best things as we get introduced to graph sheets. We use these concepts along with a few other concepts like scattering the data points or understanding the outliers from the Box Plot.

EDA is just one part of Data preparation, one shall also get to learn about Data cleansing and feature engineering in a detailed way. One needs to understand that this step takes at least 60% - 80% of the efforts in the process of Data Science projects if the data is cleansed properly and is completely aligned as per the requirement then one shall move to the next step.

In this step, the concept of Model building and its working is done, one gets to understand the process of Data Mining which includes the understanding of the concept of Machine learning to a depth of Supervised or Unsupervised learning and forecasting.

This is now followed by an Evaluation of the models to check the accuracy and errors if any.

Once the process is followed perfectly then comes the Deployment of the project followed by Monitoring and maintenance.

This stepwise approach when followed ritually benefitted most of the Data scientists and they are referring to these Data science Mindmaps just to feel abreast so that none of the phases are missed while working on any size project.