So, You are a beginner and planning to learn Data Science?. First of all, I would like to say- “Great Decision”. Data Science is a lucrative, secure, and most demanding career. But are you confused and wanna know the Best Way to Learn Data Science for Complete Beginners?. If yes, then stay with me till the end of this article. In this article, I will discuss the best way to learn data science for complete beginners and Step by Step guide from scratch to skilled data scientists.
There are various options available for learning data science like go to University, following a Bachelor’s or Master’s in Data Science, get into a Boot-camp program, or learn it by yourself.
But as a beginner, the easiest way to learn data science is to learn by yourself. Because a lot of material is available online. Then why go to university and pay high fees?. Right?
So, you got answer to the question-
But, the next question you might have- “From where to start learning?” or “What to learn first for data science?”
So, before I answer to this question, let’s have a look at mandatory skills for Data Science.
Skills Required for Data Science-
- Statistics
- Mathematics
- Programming Languages
- Database Management
- Data Visualization.
- Machine Learning
- BigData
So, these are some must-have skills for a data scientists. Now let’s see in what order you should start learning these concepts-
Data Science Career Path for Complete Beginners-
Learn Statistics
You should have Statistics knowledge that includes statistical tests, distributions, and maximum likelihood estimators.
Knowledge level- Advanced
Resources to Learn Statistics
1. Statistics with R Specialization
2. Statistics with Python Specialization
3. Data Science: Statistics and Machine Learning Specialization
Learn Programming Languages
Programming knowledge is a must-have skill for a Data Scientist. As a beginner, start with Python. Once you are comfortable with Python, then learn R programming.
Knowledge level- Advanced
Resources to learn Programming
1. Python for Everybody
2. Python for Absolute Beginners!
3. One Month Python
4. Python 3 Programming Specialization
5. R Programming
6. Data Science: Foundations using R Specialization
Learn SQL
You should have knowledge of how to store and manage your data in a database. That’s why you should have an understanding of SQL.
Knowledge level- Basic
Resources to learn SQL
1. W3Schools
2. Excel to MySQL: Analytic Techniques for Business Specialization
3. Learn SQL Basics for Data Science Specialization
Learn Machine Learning Concepts
You shouldn’t need to know how machine learning algorithms work. But You should have basic knowledge of Machine Learning Algorithms.
These are some important algorithms of ML, you can learn- principal component analysis, neural networks, support vector machines, decision tree, logistic regression, and k-means clustering.
Knowledge level- Basic
Resources to learn Machine Learning
1. Machine Learning (Coursera)
2. Machine Learning with Python
Learn Data Visualization Tools
As a Data Scientist, you have to showcase your findings in a visual form, so that stakeholders can understand them properly. That’s why the knowledge of Data Visualization is important. And for that, you should be familiar with data visualization tools like ggplot, matplotlib, Seaborn, and D3.js.
You should have knowledge of various Reporting tools like Tableau and power bi.
Knowledge level- Advanced
Resources to learn Data Visualization
1. Data Visualization with Python
2. Data Visualization with Tableau Specialization
3. Tableau 2024 Certified Associate Exam Guide A-Z (w Datasets)
Gain some knowledge of Big Data
You should have a good understanding of Big Data concepts like Hadoop, Hive, Pig, Spark, etc.
Knowledge level- Basic to some Advanced level
Resources to learn Big Data
1. Big Data Specialization
2. Hadoop Developer In Real World
3. Big Data Hadoop Certification Training
Join Kaggle Competition
Now you have enough data science skills. Now it’s time to check your ability. Join Kaggle DrivenData Competitions and challenge yourself.
Have Some Projects
Grow your data science skills by doing some Projects. It’s time to start working on some Real-World projects. Projects are most important in order to get a job as a Data Scientist.
The more projects you will do, the more in-depth understanding of Data you will grasp. Projects will also provide more privilege to your Resume.
Get Data Science Project Ideas Here.
Connect with fellow Data Scientists
Join data science communities, and stay up to date with the latest news related to data science.
Make a Strong Resume
The next step is to build a Strong Resume. Your Resume is the first impression for any recruiters. No matter how skilled you are, but if your resume is not attractive, sorry you will not get an interview call. That’s why you shouldn’t ignore your Resume.
If you want that your resume will get more privilege than others, then you should keep these things in mind-
1. The template of your resume should be classic.
2. Avoid templates with so many graphics. It gives a bad impression to the recruiter.
3. Don’t hesitate about white spaces. That means don’t try to fill the full page with text.
4. Leave some white space that looks clean.
5. Don’t write a long text like a story. It should be precise and simple.
6. Mention only the most important Data Science Projects. Don’t mention very basic projects.
7. After finalizing your resume, you need to check for grammar and spelling mistakes. You can check it on Grammarly.
Congratulation!
Now you are ready to apply for Data Science Jobs!
That’s all!. If you follow these steps and gain these required skills, then no one can stop you to land in Data Science Field.
Now it’s time to wrap up!
Conclusion
In this article “Best Way to Learn Data Science for Complete Beginners”, I tried to give you a complete road map for Data Science. If you have any doubts or queries feel free to ask me in the comment section. I am here to help you.
All the Best for your Career!
Happy Learning!
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Though of the Day…
‘ It’s what you learn after you know it all that counts.’
– John Wooden