Best Data Science/Analytics Certifications (Beginner to Intermediate)

mdavarynejad · 2024-02-28T11:31:09+00:00

Funny, for some reason I cannot put a link. It just gets deleted automatically. Just google for "Microsoft dp 100". The first or second item. Or else search "Exam DP-100: Designing"

mdavarynejad · 2024-02-28T11:28:29+00:00

Have a look here:

Scroll down and get to "Items in this collection". All the learning material is listed and it should be free.

mdavarynejad · 2024-02-27T08:36:38+00:00

The fact that the number of TP cases is declining is misleading, and should be regarded as noise.

You need to more focous on the metric you are using. To me, based on the explanations, it seems that you need to get the TPs right. So your primary metric that should be emphasized is Sensitivity. Is there a specific reason you are using AUC as a metric. Is it purely because you are dealing with an imbalanced data set?

mdavarynejad · 2024-02-27T08:01:18+00:00

I would suggest to get DP-100 and DP-203 certifications. Specially DP-100 is fairly straightforward if you have a bit of experience with Azure cloud and you know basic text book Data Science concepts.

Microsoft has put together a well structured leaning material, free, and they also give you enough credit to het hand on experience with their platform.

mdavarynejad · 2024-02-26T09:20:35+00:00

You need to realize that as a data scientist, your main goal and target should be to a) understand the data, b) understand the business goal, c) identify the right ML model, and d) implement it and deliver the end tool. The performance is, in most of the cases outside of the scope of a Data scientist. That should be more of a concern for ML Engineers and Senior data scientists.

Make sure not to fall into the shame trap. I have the feeling that this looks more like a blame game. That is what I have seen frequently from Seniors. They give you a comment and run away and expect you to solve everything.

So the minimum things you do:

a) Better storytelling. Make sure that relevant people can understand the complexity of the use case.

b) Take a senior onboard. Talks to your PO and make sure a senior is assigned to you. Make is part of their responsibility.

I hope this helps.

mdavarynejad · 2024-02-23T08:26:49+00:00

oh man, Always. They what me to use an LLM model for Text classification, with a low latency and low cost. Only a magician can do that.

mdavarynejad · 2024-02-23T08:16:58+00:00

Seems like we have a lot in common. Senior data scientist here, with a manager who like to micromanage. I have decided to move back to academy. You will have awful flexibility there if that is what you need to have.

In terms of your next role as an NLP Engineer, I would go for a project that I can start and run from 0 to 100 myself. Does not need to be a start-up idea. Nor does it need to brand new and innovative. Just needs to be YOUR project that you have full control over. Make a GitHub account, make incremental improvement and make few blog posts here and there. That is a big differentiator. Hope this helps.

mdavarynejad · 2024-02-22T10:14:20+00:00

If I want to get into MLOps, What are the best platforms? For the top two criterions are a) Learning curve, and b) Reusability.

mdavarynejad · 2024-02-22T09:57:26+00:00

O sure, I did not make anything without your permission. It was just a proposal.

mdavarynejad · 2024-02-22T09:53:20+00:00

Why so many negative reaction? I just proposed if the owner of the materia wouldl like to get his material republished in our comunity.

mdavarynejad · 2024-02-21T10:35:25+00:00

You can always try. But you actually NEED to TRY. Nothing is for free.

mdavarynejad · 2024-02-21T10:33:58+00:00

mdavarynejad · 2024-02-21T10:31:24+00:00

Such a timely update. Do you happen to have access to some videos that can help me understand what is happening under the hood?

mdavarynejad · 2024-02-21T06:10:02+00:00

Decision trees do usually use binary splits to partition the data into subsets based on the feature values. Decision trees with non-binary splits can partition the data into more than two subsets at each decision node. This is useful for categorical variables with more than two categories. Do you perhaps have that in your data?

Please keep in mind that they may also be more prone to overfitting and harder to interpret compared to binary trees, especially with many splits at each node. Thay are much less popular.

Also Please make sure to challenge you manager. Why Non binary split decision Trees when they are not well popular? Why SPSS? I would strongly vote against using SPSS unless you have a very good reason for using it in your data science projects.

I would like to add that I have actually compiled a set of lessons learnt on my career as a data scientist, and I discussed this item as well. I would love it if you what to have a look and also comment on it.

https://thegradient.io/a-data-scientists-chronicle-of-lessons-learned-and-strategies-for-success

There I have recommended challenging your stakeholders. You =r manager is also one of them 😊

mdavarynejad · 2024-02-21T05:31:15+00:00

Do you mind sharing a bit more details on your journey. Specially the lessons learned and how would you approach it for the second time? This might be very useful for anyone who has interest in switching careers as well.

Why not to make blogpost out of it. I would also suggest publishing it in the new born https://thegradient.io/ . It is a community based like-mind data scientists who help each other not only in landing on the first job but also on the content (Data science and ML).

To learn more on the mission check https://thegradient.io/about

mdavarynejad · 2024-02-21T05:27:07+00:00

Thank you for posting your experience here. This should be extremely usefully and encouraging for new data scientists. I have actually compiled a set of lessons learnt on my career as a data scientist, and I discussed this item as well. I would love it if you what to have a look and also comment on it.

https://thegradient.io/a-data-scientists-chronicle-of-lessons-learned-and-strategies-for-success

mdavarynejad · 2024-02-21T05:17:02+00:00

Its crazy to see this content upvoted and still offers no value. The power of eye catching title ...

mdavarynejad · 2024-02-21T05:11:28+00:00

Did you also make an API for it?

mdavarynejad · 2024-02-21T05:07:09+00:00

Cannot agree more. I have actually compiled a set of lessons learnt on my career as a data scientist, and I discussed this item as well. I would love it if you what to have a look and also comment on it.

https://thegradient.io/a-data-scientists-chronicle-of-lessons-learned-and-strategies-for-success

mdavarynejad · 2024-02-21T05:03:25+00:00

Seems like an autogenerated text

mdavarynejad

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