Data science is one of the most evolving fields where a lot of things are happening. In fact, being a Data Scientist is one of the most lucrative career options in the present time.
With a huge demand for data scientists, choosing data science as a career option offers a lot of scope and opportunities for the future.
Why Learn Python With Data Science?
Python has garnered a lot of interest in recent times as a choice of language for data science and data analysis. Understanding Python is, in fact, one of the valuable skills needed for a data science career.
Among the reasons which make learning Python with Data Science an excellent decision include:
- It is an open source language that is free to install.
- Features an extensive online community.
- Equipped to become a common language for data science and production of web-based analytics products.
In addition to learning Python with Data Science, the journey to becoming a successful Data Scientist should also include a lot of other technical and soft skills. If you’re looking to make a flourishing career in this field, here are the top 3 tips to improve your data science with Python skills:
1. Make a Data Science Portfolio
As an aspiring data scientist, one of the most important requirements is to build a portfolio. These projects under this portfolio should include different datasets with the findings and interesting insights that you’ve made as data scientists.
Remember that your portfolio need not require a theme. All you need to do is find the datasets that catch your interest and put them together in new and innovative ways.
Building such portfolio allows you to collaborate with fellow data scientists and also helps you in building a strong resume for yourself that reflects your preparedness & willingness to learn the fundamentals to learn data science with Python as the programming skill.
While you work on building a portfolio, do not forget to brush up your technical competence as well.
2. Learn How to Clean Data
One of the main tasks of Data scientists is to analyze the data, get a model from the same, and predict interesting results based on this. However, many times, the data available to data scientists is not clean or contains unwanted values.
It is, therefore, imperative for the data scientists to learn how to clean the data as a part of their work profiles.
3. Work on Applying Advanced Data Science Techniques
The data science journey of aspiring data scientists is full of constant learning, but there are several advanced courses available that you can enroll for to ensure you’ve covered all the basics of the field.
Additionally, take the effort to learn all the advanced data science techniques including Classification, Regression, and k-means clustering models along with machine learning concepts and creating neural networks.
How to Learn Data Science With Python
As a beginning step, you’ll have to find the right course to help you learn data science with Python programming. Well-curated data science training can be extremely handy and provides a user-friendly introduction to the subject of Data Science.
Upon completion of a data science course, you’ll be able to write your own Python scripts, perform hands-on data analysis, and start creating your own data science projects along with collaborating with other data scientists.
What Will You Learn in This Course
- Python basics including the types, expressions, and variables.
- Python data structures including lists and tuples, sets, and dictionaries.
- Python programming fundamentals such as loops, functions, objects & classes, conditions & branching.
- How to work with data in Python (loading data with pandas, reading & writing files with open, and more).
The Way Ahead
As per estimation for the year 2019-20, the overall population with analytical skills is going to be more than a whopping 2.5 million. This reflects the huge scope of the data science in the coming years offering incredible opportunities to aspiring data scientist candidates.
The above-shared tips to improve your data science with Python programming skills can be further instrumental in enhancing your career prospects as data scientists.