Tips for those of you who want to study and work in the scince data field

 Tips for those of you who want to study and work in the scince data field

Along with the development of the times, the data scientist profession is increasingly needed, not only in large companies such as google amazon etc. now there are also many non-IT companies that need this profession.

they all understand the importance of data and data science so that they are competing to get more income by hiring data scientists.


but what happens in the field, this profession is still very quiet of enthusiasts, as evidenced by their salaries which are the highest among the salaries of other jobs in the IT field.

Lots of people who want to learn data science, but they are confused about where to start. therefore now anaktik.com will provide tips for those of you who want to study and work in the field of data science

1. Determine the field you want to target

a lot of work related to data science. Example :

•     Data Analyst
•     Data Engineer
•     Machine Learning Engineer
•     Data Scientist General
•     AI Engineer

Get to know each of the jobs, such as the advantages and disadvantages, the job desk, the salary range, etc. (the higher the salary, the higher the responsibilities).

after that decide which field you want to study and make yourself motivated to pursue that field, because it is very difficult to learn if we don't have motivation.

2. Take the Course and Complete it

Now that you have decided what field you want to take, you have to know more about the role you take, what to study and so on. After that start learning. The market demand for Data Scientists is very large, it is directly proportional to the number of services that offer training for this profession.

there are thousands of courses and studies out there ready to teach you, you can study whatever you want. Finding the material to be studied is not difficult, but you will still not understand it if you don't try it.

When you take a course, look for the one that best fits the field you want to go to. and do everything assigned by your instructor.

For example, if you want to become a machine learning engineer, you could take a machine learning class with Andrew Ng. Now you must be diligent in following all the course material provided in the course. This also means doing all the assignments given, because everything is useless if you just buy the course and then next and next until the course ends. one of the best data science courses you can find on udemy

3. Select focus tools / main programming language

As I mentioned earlier, it is important for you to gain experience from each given tutorial until the last tutorial. the next question that often arises is, which language should I learn? or what tools should I use? Which one is better?

This is probably the most popular question asked by beginners. The easiest answer is to choose one of the tools and languages ​​and then start trying, because by trying you can find out which tools and languages ​​are best for you.

4. Focus on practice and not just theory

During courses and training, you must focus on the practice of what you are learning. This will help you not only understand the concept but also give you a deeper sense of how it will apply in reality.

Some tips that you should do when taking courses:

• Make sure you do all the exercises and assignments to understand the application.
• Work on several different datasets by applying the same techniques as taught. this can open your mind if you previously did not understand the purpose and purpose of the tutorial.
• Look at the problems you have in the field, then do your own analysis. This will hone your skills in the field of data intuition and it is a skill that is highly sought after in the era of big data

5. Practice your public speaking skills

many people underestimate this skill and they end up being rejected from work. they think that if they are experts in the field of data science, they will easily get a job. This is actually a myth. Even if you do get an interview, you will be rejected because your communication skills are poor.



Try one of these activities; Gather all your friends who have good communication skills and have them listen to you explain the insights from the data after that ask for honest feedback.



Communication skills are even more important when you are working in the field. Because actually the information you get from data will be consumed by company officials. and you have to present it in front of them, if your communication skills are not good, will they understand what you are saying?

6. Look for Relationships or Partners

During a very exhausting study period. There will definitely be a point where you will feel very bored and think I better just give up.

That's why it's important that you build relationships between other data science activists so that you have friends to share, you can attend industry events and conferences, meetups in your area, participate in hackathons in your area - even if your skills are low. You never know who, when and where your friends will help you!

In fact, this relationship will be very beneficial when you are going to enter the data science industry. You can meet people in your area who are actively working, which gives you the opportunity to network and build relationships with those who will ultimately help you advance your career.