Landing a job in AI

It is all the work that decides your future and the future is now.

When has this started?

How did I make it?

Why did I choose this?

The days are never the same. The only thing that remains constant is the change. Change is for the better and to become the best of yourself. I always wanted to make something more creative, and amazing and to be part of an innovative future. I choose to become a data scientist because I always know that I can make it happen as everything has to start at one point. When I started no one believed (except few) that I would be able to make it so I just made it.

Some of the qualities that made me achieve it are:

1. Passion
2. Dedication
3. Time management
4. Guidance and mentors
5. Resources
6. Practice, practice, practice
7. Perseverance, persistence and patience
8. Being optimistic

Data analysis was part of my business degree and coming from a computer science background made me firmly believe that I would be able to learn it and do it well.

It started when I got to know that I wanted to do much better than what I was doing in my previous job. I can do much better, I’m more skilful and can adapt and upgrade to new technologies.

I found data science interesting becomes it is everywhere and brings solutions to never known problems like how did voice assistants come up, how google home works and how is language translation possible and how is a machine able to ask us questions and give relevant recommendations. The constant upgrade and work going on as we are doing it.

So what did you find interesting and amazing? What interests you?

How about you invent something new? Yes, it is more intriguing. Isn’t it?

I started looking for resources. There is no one-stop solution definitely, I have to go through different sources to understand all the relevant topics as it is an ocean. I have done my full-time course at some institutes also online at Almabetter and some other video lectures from youtube, udemy, coursera…many others.

Some of the important things you have to note when you are on a data science journey are to possess problem-solving skills, statistical skills and use creative thinking to bring the solution out. Learn, practice and do more projects, hackathons, etc.

Time always starts ticking without knowing when it is going to end. Just keeping the goal in your mind is enough and being present knowing that you can make it. It might be late then it is not impossible. We should always make time for the things we want to achieve or spend it. Time is valuable so use it wisely and spend it with the things or people so you don’t regret it later.

There are many rejections before I made it. It almost took me 2 years to land a job in it. It took me one year to completely understand the basics of data science and improve more on the skills by building more and more projects that is when I understood how much the practice or real work helps in making us understand or involve more and deep dive into it.

Believe in yourself!!!

Anything starts small so start it and take it wherever you can. It is your own flight. Land it safely then be cautious before you fly it.

There are always some distractions around so I just focus on what is necessary, important and what would I wanted to do. There is some habit rule like you do the things regularly for few days(21 or 66 or 90 days) it becomes a habit. When anyone wants to try something we can do this. Yes don’t you think it works even if we are lazy because on someday we will automatically go for it. So smaller chunks daily, bigger trunk someday.

Photo by Brian Garcia on Unsplash

If you want to know how to solve a problem using data science refer the link

Going to the technical part of it. The important subjects that need to be covered when you want to be called a good learner or become a full-fledged data scientist are:

1. Statistical knowledge
2. Programming(Python is preferred and my favourite too)
3. Machine Learning( Supervised, Unsupervised mainly focused and reinforcement can be later)
4. Deep Learning(The visual effects or images are present here. The most interesting, demanding part is here)
5. Databases like SQL /NoSQL database like Mongodb
6. Tableau for data visualization
7. Quizzes, Hackathons, Real-time projects..etc

I have already started sharing my knowledge and would like to know if there are any queries or any feedback. If you find this helpful please share it with someone useful and can follow the blog for more articles which would encourage me in writing more insightful articles.

Bring your dreams to light. Be brave.

Dream big, achieve big