I have enrolled in scaler data science course recently. And after completing a couple of months studies with them here are the Pros and Cons for me: Pros: Very structured course and relevant topics. Along with really good assignments after each class. Instructors are really good. Until now I have onRead more
I have enrolled in scaler data science course recently. And after completing a couple of months studies with them here are the Pros and Cons for me:
Pros:
- Very structured course and relevant topics. Along with really good assignments after each class.
- Instructors are really good. Until now I have only interacted with Mohit Uniyal, and I think he is really good. He is very thorough and amazingly patient while answering doubts.
- Teaching Assistance support is another great resource. You can reach out to them anytime via chat or video call. So that’s very handy.
- The dashboard is laid out really well too. The options to view class recordings any time, making bookmarks, discussion, scaler support access. Very neat!
- I have heard they have good placement and career support as well. I haven’t availed or experience this yet first hand since I am only 2 months in the course now.
Cons:
- Quite expensive course for sure, but given the quality and other equally and more expensive courses in the market such as upgrad, I am not surprised.
- Features like mentors are not very helpful, as even many mentors are still figuring out their career.
- A lot of spam from scaler. OMG! like you name it, Email, Whatsapp, Slack, so much spam from scaler and other learners.
- Lack of quality network building. Eventhough scaler has the above platforms where learners can connect, it still fails to help learners network. I know it is a hard thing, but I hope scaler can come with something where learners can benefit from each other.
Fell free to each out to me on LinkedIn if you have any other questions – https://www.linkedin.com/in/-prince-jindal/
See less
Nowadays, Data Science and Artificial Intelligence are the two most important technologies. In contrast, Data Science uses Artificial Intelligence in its operations. Data Science and Artificial Intelligence are used correspondently. Data Science may come up with some aspects of AI but does not refleRead more
Nowadays, Data Science and Artificial Intelligence are the two most important technologies. In contrast, Data Science uses Artificial Intelligence in its operations.
See lessData Science and Artificial Intelligence are used correspondently. Data Science may come up with some aspects of AI but does not reflect it. Data Science is the current ruling technology that has conquered industries worldwide. It brought the fourth industrial revolution to the world today.
Data Science involves various fields like Statistics, Mathematics, and Programming. So, a data scientist must be proficient in understanding data trends and patterns.
For doing a data science course, you don’t need to be from a technical background. So if you want a better career opportunity go for it. Data Science courses are budget-friendly, and many institutes provide Data Science courses with affordable fee structures. Nowadays, data science has a high demand in all domains. So, rather than taking a high payable course, you can take a data science course.
Artificial Intelligence is the Intelligence technique that is possessed by machines. It is modeled after the natural Intelligence possessed by animals and humans. Artificial Intelligence makes use of algorithms to perform autonomous actions.
Artificial Intelligence also uses several software engineering principles to develop solutions to existing problems.
For AI, you must have programming knowledge. It is more technical than a data science course. A course in AI is much costlier than a Data Science course.
1. Data Science is a long process that involves processing, visualization, analysis, and predictions. On the other hand, AI is the execution of a predictive model to predict future events.
2. Data Science comprises various statistical techniques, whereas AI uses computer algorithms.
3. Data Science involved more tools than in AI because Data Science involves multiple steps to analyze data and generate perceptions.
4. Data Science is all about finding hidden patterns in the data. AI is about relating autonomy to the data model.
5. Data Science is for build models that use statistical perceptions. In contrast, AI is for building models that reproduce cognition and human understanding.
6. AI involve a high degree of scientific processing as compared to Data Science.