Source: Deep Learning on Medium
At the beginning of the year, I challenged myself to learn and apply data science in 6 months. On average people need at least 3 years to get into the data science field. Through my fingerprints during this year passed a lot of projects. I wanted to apply everything I learned immediately. Until June I was an employee and from June I am one of the first self-made data science women in the world. My goal list for this year was really long and now when I am writing it, I really can’t believe how much I succeed in one year.
I read somewhere that McKinsey says by 2030, intelligent agents and robots could eliminate as much as 30% of the world’s human labor. The World Economic Forum contends machines will replace more than half of the world’s current workplace functions by 2025. Also in 2019, there will be 75x more data than in 2018. Power of data is present and future.
A big issue right now is that while more and more companies are committing more heavily to data-driven product development and their data teams, there are very few examples of folks deep in their careers who are pure data scientists. And that just makes it a lot harder for folks who are passionate about data science and happy with their current roles to have the confidence they should have that those roles and that career progression will be there. I’d also add that I’ve found data science to be a field where you can add a ton of value relatively early in your career, in part because the field is in its early days, and in part because the nature of the work is exploring the corners of what your product does and can do that no one else has looked at. These were the main goals why decided to change my career path to data science. My mission is to help decision makers gain more profit with data science and machine learning insights.
I also think it’s wonderful that data science prepares you well for a variety of ways to add value in tech, and I also think you’re seeing the lines blur between data science and product management and other related roles at a lot of companies. I can say that as a data scientist you are the bridge that connects developers and managers to go for the same goal, which is gaining more profit and revenue for the company.
Here I will list everything I succeeded in 2018:
- Learn Tableau and become Tableau expert
- Learn Python and master it
- Go to WebSummit and meet at least 5 data scientists in person
- Do projection for Football World Cup
- Learn data science every day without pause (I am currently on the 361 days of learning and coding in data science)
- Write at least 10 blogs
- Made than more 10 machine learning projections (breast cancer dataset, content analyst classifier, fashion classification dataset, credit card fraud detection
- Finish my Data Science roadmap with all tutorials
- Post regularly on Linkedin
- Give more than 200 people in Belgrade lectures how you can become a data scientist
- Have 2500 followers on Linkedin and at least 150 blog readers daily
- Mentor at least two data science enthusiasts
- Travel to more countries
- Make my website easydatascience.com with my online tutorials and business coaching for data science enthusiasts
- Work with clients for UK, UAE and USA only
- Become part of US Embassy in Serbia and part of women in tech
- Get into Micromasters on MIT in the field data science and statistics
- Surround with only people who are good for me
- Bough my awesome HP laptop for data science magic
- Finished Machine Learning course A-Z, Machine Learning Practical
- Finished Tableau Basic, Tableau Advance and Tableau expert
- Open Kaggle account and finished Titanic Disaster Machine Learning dataset
- Open my Data Science company
- Having a good relationship with my family
- Finished Python Bootcamp and Automate the boring stuff with Python
- Did more than 20 real-world exercises
- Teach more than 50 people Guerilla Marketing Strategy
- Let go my first startup Petrucci Elegance and give my mum try with it
- Moved to live closer to the city center
- Learned surfing
- Learn peat methodology and communication skills for managers
- Work as networker on Web Summit for chairmen, executive officers, partners and so on
- Go first time alone on the trip
- Read more than 24 books in data science and marketing field
- Do data science projects in fintech, sport, and marketing industry
- Work remotely and leading different teams
- Become part of Django Girls community and made my first Django website
- Attended Python conference in Belgrade
- Data Science and Guerilla Marketing mentor at Faculty of Economics
- Become one of the speakers on Kopaonin Business Forum
- Meet, learn and apply tips and tricks from my mentor Jelena Ristic, Slavo Popovic, Neva Rajkovic, Hadelin de Ponteves, and Kirill Eremenko
- Get first clients on Upwork and Toptal
- Become a blonde girl
- Specialize in Machine Learning and code every day until 25th January, as part of my 100 days ML code.
- Write as blogger and data scientist in different relevant publications in the data science field
- This only 1/3 of the list that is accomplished in 2018.
What I will do in 2019?
- Write 365 blogs about data science, machine learning, and AI
- Vlog challenge 30 days from 1st January
- Sleeping 5hours 30-day challenge — — – polyphasic sleeping
- Record more than 50 screencasts with python and Tableau
- Learn and apply NLP and Deep Learning
- Do more than 10 machine learning projects in digital-health, sport, marketing, fintech
- Go to Thailand for vacation
- Try skiing
- Become Machine Learning consultant and Python expert
- Learn D3.js
- Read 25 books about machine learning and data science
- Write book Applied NLP with Python with Packt
- Publish Tableau 2019.1 for Data Science course with Packt Publishing
- Write a book “Hacks for becoming a data scientist in 6 months”
- Get scholarship and mentoring from TopTal as a women leader
- Help Trounceflow become a trusted partner in emerging markets
- Get my own flat in central Belgrade
- Help Faster Capital to grow in Serbia
- Have one big client
- Have excellent panel at Kopaonik business forum
- Make Data Science Online Bootcamp for women
- Finish Micromaster on MIT
- Go to AI MIT workshop for 6 weeks in Boston
- Go and visit my mentor Slavo Popovic in Miami
- Become Data Science first Unicorn in Serbia
- Have 1000 readers on my blog daily and 10000 followers on Linkedin
- Go to Data Science GO Conference in San Diego held by Super Data Science Serbia
- Make Linkedin bot
- Visit NY, LA
- Go to Egypt
- Make podcasts with Milos Pistolic
- Mentor more than 10 women who want to become a data scientists
- Go to Web Summit as speaker
- AI & Big Data Expo Global, London (Apr 25 — Apr 26, 2019)
- Go to at least 3 conferences as a Data Science speaker
- Go to hackathons in data science and machine learning team
Have my team of the data scientist in Belgrade
You now know what I did in 2018 and get ready for big stuff coming in 2019.
If you are still scared to get into data science you can see my story how I became a data scientist, so go for it. If you are wondering what is my secret, I will tell you.
- I am learning coding and data science every day at least 1h a day. There is study If you learn and apply something for 2 years in a row you will become an expert. I don’t want to wait 5 years to become a consultant and expert. I am already a data scientist after 6 months, even everybody told me that isn’t possible because I don’t have Ph.D.
- I am learning, applying and having mentors who will help me to succeed in my biggest challenge — TO BE ON FORBES LIST AS SELF MADE WOMEN UNDER 30. #FORBESUNDER30 — — — -
- I have a special sleeping habit. I am sleeping from 1.00- 6 am and I have one nap between 6.00pm -6.45pm
- I meditate every day and night for 30 minutes. I am applying manifesting methodology and peat methodology every day.
- Writing my ideas in dairy every day before sleeping.
- Spending my free time only with friends who are similar to me. Because you are your 5 best friends.
- Spending time with my boyfriend who is a developer and understand when I forget to sleep doing some data science challenge.
- Traveling and learning from anyone despite his education background.
- Teaching others data science and mentoring.
10. I have a strong business, marketing and economics background. You can say I am a bridge between Managers and developers. I can explain complex data science stuff easy and understandable to anyone. I always test it on my mum, If she understands me, then everybody will. She isn’t from data science field.