If you are confused about answering which technology to learn first, whether to go with Data Science or Machine Learning, you have landed at the right page. The article will clear all your doubts to give you a better understanding of both the technologies.
Introduction
If you are deeply indulged in the tech world, the terms Data Science and Machine Learning have never escaped your attention. If you are thinking of learning and developing new skills, both the technologies have their own career scopes.
According to the Gartner report, “Out of the 10 lakh registered organizations in India, 75% have invested or are planning to invest in Data Science and Machine Learning”. So there shouldn’t be the second thought about learning these revolutionizing technologies.
There are top platforms like Global tech Council that offers data science certification and Machine Learning certification training and courses, making you ready for an industrial revolution.
Data Science vs. Machine Learning
Before understanding what one should learn first, let’s figure out what are the differences between the two most heard technologies of 2020. As these terms often overlap, to have a clear idea about the two is crucial.
What is Machine Learning (ML)?
ML is an application of Artificial Intelligence, where machines can learn by themselves without explicitly programmed. As machine learning is a subset of AI, it enables systems to learn and improve automatically. It makes software applications more accurate and precise in predicting outcomes.
The best example of this technology is customer-based product recommendations based on one’s past experiences. Facebook, Amazon, Netflix, and other top companies are using ML algorithms for customer-based product recommendations, real-time analysis, and for other various purposes.
Data Science
It is a concept that is used to handle big data. It is a mixture of various algorithms, tools, and ML algorithms to discover hidden patterns from unstructured data. A data scientist is one who gathers data from multiple sources and applies ML algorithms to collect critical information that is beneficial for organizations.
From the above definitions, it is clear that the significant point of difference between both the technologies is that Data Science generates insights, and ML produces predictions. We can say that ML is an integral part of the Data Science as Data Science makes use of ML, for analyzing data and future predictions.
To start a career in data science, check out Global Tech Council for data science certification and training courses.
Required Skills Sets
Due to the lack of niche data skill sets, there are endless job opportunities in both these domains.
If you decide to choose a career path in Data Science, you can be a
- Data Analyst
- Data Scientist
- Data Engineer
- Data Architect
- BI Analyst
Key Skills for Data Science
- Programming skills in Python and SQL
- Able to perform analysis on a large set of data
- Dealing with data wrangling
- Familiar with machine learning methodologies
- Data Visualization
- Monitor analytics and metrics results
- The combined knowledge of soft, technical and practical skills
If you talk about career opportunities with ML, these are the options.
- ML Engineer
- Data Scientist
- Human-Centred Machine Learning Designer
- Business Intelligence Developer
- NLP Scientist
Now, since it is clear that you can fill up many roles in both the domains, let’s figure out what are the required skills.
Key Skills for ML
- Profound knowledge of data structures
- Data Modeling and Evaluation
- Implementing ML algorithms is must
- Probability and Statistics
- Sound Knowledge on hadoop sub-projects
- Knowledge of various analysis tools
What to Learn First, and How?
ML and Data Science are excellent skills, and it wouldn’t be right to say which one to learn first as both technologies have their own scope and career opportunities. It solely depends on the individual’s choice to choose the course as there is no strict laid out rule, and there is no hierarchy to follow.
To become a machine learning expert or a data science developer, check out Global Tech Council, one of the best platforms that imparts the best training and online certification courses in machine learning and data science domain, covering fundamentals and all high-level concepts.
Data Science developer course covers the core concepts of Data Science with advanced topics like neural networks, R programming, machine learning, and more.
ML course will equip you with the most effective machine learning techniques, data mining, statistical pattern recognition, covering not only the theoretical part but the practical knowledge.
Conclusion
No matter which technology you learn first, there is non-stop growth in career opportunities. Skilled professionals in the domain of Data Science and ML are high in demand with less availability. If you are ready to accelerate your career, why wait! Get in touch now.
Want to explore more and keep yourself update with these latest technologies? To become a data science developer, sign up for a data science certificate online today. If you choose to be a machine learning expert, check out the training and online courses on the Global tech Council.
Leave a Reply