Over the last five years, the need for data scientists and analysts has skyrocketed. Scripting languages, large data, SQL databases, and machine learning are all abilities that employers seek. Big Data has been one of the hottest subjects in technology for years: Data Scientists are in high demand, and colleges are increasingly offering specialised Data Science Master’s degrees.
Why study this course
Develop your practical abilities by working with real-world situations and datasets to learn a variety of in-demand skills for extracting and processing ‘big data.’
This course will provide students with a theoretical understanding as well as hands-on experience with data science and analytics methodologies. You’ll learn how to extract and handle ‘big data,’ as well as how to use modelling tools to assist businesses and government agencies in making better decisions.
You will be well prepared to advance into several professions in data-intensive companies or a related research career after completing the course.
Top reasons to Study this Course
Master key data science and analytics skills
You’ll learn how to use and apply a variety of technologies, structures, techniques, tools, and approaches, such as data warehousing and mining, distributed data management, and relevant AI and machine learning techniques.
Develop your problem-solving skills
You’ll concentrate on generating real-world solutions to problems related to changing IT architecture and growing data quantities, as well as gaining a thorough understanding of the underlying theories and approaches.
Gain industry-insider knowledge
You’ll hear from industry experts and have the chance to see data science jobs and analytics teams’ workspaces.
Get your hands on the most important software and languages.
You’ll use R, Python, SQL, Simul8, Palisade Decision Tools, Tableau, and Oracle, among other industry-standard applications. You’ll gain a better understanding of algorithms and quantitative approaches like Al, ML, OR, and Advanced Analytics, which may be used to analyze and mine data and construct decision models in a variety of applications.
The advantages of pursuing a master’s degree in data science and analytics (MSc)
1. Data Science is exciting – and data fuels the future
For decades, technical advancements were primarily driven by increased processing power, which opened up new possibilities. As traditional hardware reaches its physical limits, attention has shifted to software-driven applications.
Because of its enormous potential, data has been dubbed “the oil of the digital economy” (Wired); you could say it will power our future. Data analysis enables the development of entirely new generations of technological solutions, such as Data Science and Machine learning and artificial intelligence (AI) are two examples of areas where significant progress has already been made. Advanced statistics, on the other hand, drive new advancements in other areas: For example, data on user behavior and predictive analytics assist businesses in improving the user interfaces (UI) of their software products, and detailed performance analyses assist businesses in tracking the return-on-investment (ROI) of their marketing campaigns and making more informed decisions.
2. You have many career options
In a wide number of businesses, data and information have become essential resources. Many new possibilities have arisen as computing power and digital storage have increased, which were previously unimaginable just ten to fifteen years ago.
However, such innovations aren’t limited to the technology sector.
That is why data is vital to all organizations and levels. Data professionals are needed in banking and finance, automotive, energy, healthcare, transportation, retail, and practically every other industry. And, because data is at the heart of all choices, from tiny regional offices to the boardroom, graduates from Data Science programs will be actively involved in key strategic decision-making processes.
The job names you’ll come across are as varied as the responsibilities you’ll be responsible for. You will be a valued team member in various parts of an organization if you are a specialist who knows how to “crunch the figures.” The following are examples of common job titles:
- Analytics Engineer
- Analytics Manager
- Big Data Engineer
- Business Analyst
- Data Architect
- Data Analyst
- Data Engineer
- Data Scientist
- Data Visualisation Specialist
- Business Intelligence (BI) Architect
- Business Intelligence Engineer
- Statistician
3. Your job prospects are incredible!
Employers can’t find enough grads to fill their jobs because data scientists are in high demand. Universities have been boosting the amount of master’s degrees in data engineering and data analytics to meet the demand. With so many potential employers vying for their services, university graduates are now in a strong position to demand hefty compensation.
Your chances are even better if you have a postgraduate degree: According to a study conducted by job search platform Joblift, 50% of all data science job postings require applicants to hold a postgraduate degree. That means that earning a Master’s in Data Science effectively doubles your work opportunities in the sector. Furthermore, it may pave the path for you to pursue a Ph.D.
Conclusion
With an anticipated data scientist shortage, now is the time to prepare for the future. Data scientists are needed in practically every business, from health to government to publishing, to conduct statistical analysis or mine data from social media. As a result, our course opens the door to almost every field, from health to government to publishing.
MSc Data Science is for you if you are interested in addressing real-world problems, developing abilities to use smart devices efficiently, wanting to use and expand your understanding of mathematics, and wanting to use statistical techniques and methodologies to analyze data.
