Data science has created a buzz all around the world with its impeccable capabilities of solving complex algorithms and creating patterns from big data sets. It offers a vast range of opportunities for people who are looking for high paying jobs in prominent organizations. Data scientists are taking up higher-end positions in organizations, building strategic models that are helping companies get an edge over their competitors.
If you are looking for a high paying job in a domain that is continually evolving and growing, Data science is the best field for you. You can learn data science by using python courses as Python is the primary unit of data science. Many data science-related job descriptions have Python mentioned as a mandatory skill for candidates.
Why Should You Learn Python?
If you are wondering where to start, take a python training for data science job opportunities. Here are some reasons why you should learn Python if you plan to make it big in your career:
- Is easy to learn and has a wide range of applications.
- Has immense growth potential and offers high paying jobs to candidates.
- It is a versatile programming language and will help you grow in the field of data science
- It allows you to automate tasks for repetitive actions – saves time and effort.
- Helps you create machine learning algorithms.
- Offers good libraries and frameworks making web development easier
- Has a huge community base for developers, scientists and analysts.
Given the rapid development, we dig deep into the fastest-growing job roles that you can land in data science using a Python training.
Data Scientist is labelled as one of the hottest jobs in the business world. The demand for skilled data scientists has increased significantly over the last decade. From startups to e-commerce majors to tech giants, every organization is looking for candidates who can fulfil the position of data scientists in their companies.
Recently, Python has become crucial to data scientists as it has emerged as the most in-demand skill for data scientists. Apart from Python, a background in machine learning, artificial intelligence, predictive modelling and analysis, analytics techniques such as Classification, Clustering, Regression and Time Series can come in handy when applying for the role of a data scientist.
If you can make sense of complex data sets and derive useful information to create patterns connecting data within the large data sets, you should consider becoming a data analyst. Not only you will be rewarded with a high salary but you will also get to explore and learn about data statistics, automation and artificial intelligence.
Core skills required to become a data analyst include programming languages like Python or R, tools like Excel, Tableau and SQL. Successful companies like Amazon, Google, Netflix, IBM, all hire data scientists with high salary packages.
Machine Learning Engineer
Machine learning is an important part of consumer-facing technology companies that deal with a high influx of data from consumers. The job description of a machine learning engineer entails tasks such as designing solution architecture for applications, automating model training processes, testing and deployment of regular applications to establish a continuous delivery pipeline.
Core competencies required for the role of machine learning engineer include programming languages such as Python, R, a background in modern and classical machine learning techniques such as clustering, segregation, regression and neural networks as well.
Data Engineer is relatively a difficult position to fill in, given that it requires experience with Hadoop-based technologies like Hive, MongoDB, Cassandra or MapReduce. Data engineers build data pipelines and work with use cases from the pilot to the production stage.
Besides the knowledge of big data technologies, data engineers are also expected to have a good command over general purpose and high-level programming languages like Python, R, Scala and SQL. If you have a keen interest in working around big data sets and in an environment that challenges your skill sets, taking a Python course or training is a good way to begin your data engineering journey.
Python is highly important in the data science industry. Take a Python course for data science jobs, so that you have the requisite skillset and can carry out the tasks mentioned under the job description efficiently. Learning Python is much easier and simpler as compared to other general-purpose high-end programming languages. It has a smooth and linear learning curve which enables the user to understand and implement the language easily.