Data Science Courses: Know These 4 things Before Choosing One
Data science courses are all the rage right now and why shouldn’t it be? After all, for three years in a row, data scientists jobs have been named the number one in the US, according to Glassdoor. The Indian job market too has seen a 400% rise in demand for Data Scientists, making it a hot pick.
But what exactly do data scientists do? Remember that one time you looked at a product and then suddenly every time you opened social media, there it was, constantly asking you to buy it. No, Mark Zuckerberg isn’t spying on you, this is a result of some smart algorithms data scientists developed that accurately pegged your buying behaviour.
Data scientists primarily analyse raw data to arrive at actionable insights. This involves predictions and even prescriptions to dictate future action based on the data available. Before you embark upon a data science course, here are some things that will help you understand the field better to make an informed decision.
What you should know before taking up Data Science Courses –
- Understand the role of a Data Scientist
Data scientists are becoming increasingly important as businesses rely on data, now more than ever, to make impactful decisions. Terms like automation, machine learning, and big data are part of everyday vocabulary. A data scientist therefore must also have sound business and domain knowledge to accurately translate the unstructured data into meaningful insights.
Data Science in retail has proved to be a huge success with platforms like Amazon using it extensively with their digital-only interface. They use sophisticated algorithms to suggest products to users based on their past purchases and the history of other users. They also optimise their prices keeping in mind various parameters like order history, product availability, competitor pricing, etc to offer discounts and push lesser popular items.
A data scientist job description therefore, would look something like this:
This is only the tip of the iceberg, a data scientist’s work seeps into diverse industries and thus, into almost every aspect of modern life. A day in the life of a data scientist is packed with everything from research and statistics to computing and advanced analytics.
- Analyse the job opportunities available
In a report published by IBM and Burning Glass Technologies, Business-Higher Education Forum (BHEF), it was found that data science jobs are among the most challenging to fill and that employers are willing to pay premium salaries for professionals with expertise in these areas. According to Glassdoor, Data Scientists earn about INR 9,00,000 per annum making it one of the most well-paying jobs in the country.
- Take stock of the core skills required
Data science skills is an amalgamation of a variety of capabilities to be able to solve business problems. A few core skills that is included in data scientist job description involves:
Statistical Analysis: Involves making accurate calculations and predictions based on data patterns. A keen eye for anomaly detection is required while cleaning the data.
Programming Skills: Ability to write computer programmes and analyse large amounts of data is an essential skill. Knowledge of writing codes in languages like Python, SQL, R, etc is a must.
Computer Science: Advanced computing with an understanding of database systems, software engineering and artificial intelligence is a core skill set.
Machine Learning: Using algorithms to key in data that will be able to intelligently predict and take action on its own is the future of data science.
Some of the soft skills a data scientist needs to work effectively in an organisation is:
Communication Skills: Strong storytelling skills to communicate the insights from the data is required to be able to convey messages effectively. Being able to unpack complex data and make it relevant to non-technical audiences is a challenge data scientists must be prepared to face.
Business Skills: Understanding the functioning of an organisation is essential to deliver solutions and results that will have a positive impact. Solutions must be able to solve direct business problems after having understood its needs well.
Analytical and Critical Thinking Skills: A key data science skill is to be able to think critically and factually. One must be able to find analytical solutions to abstract business issues and look beyond what lies in the surface.
- Plan your Specialisation
Like with every field, specialising or choosing your area of focus will help you find jobs that fit your profile as opposed to “doing it all” under the larger umbrella of big data analysis.
Some of the areas of specialisation are:
- Data Engineering and Data Warehousing – Involves structuring data and managing its quality and storage.
- Distributed Computing – Involves implementing structures required for cloud computing.
- Data Mining – Involves the application of statistics to explore predictive models and identify patterns.
- Database Management – Involves securing the data and maintaining high volumes of complex data.
- Machine Learning – Focus on building algorithms that will help models take action on its own. Not to be mixed up with Machine Learning Engineering.
- Data Visualisation – Involves presenting the data in a visually appealing manner to make the insights more accessible.
Finally, pick data science courses that help you build foundational skills as well as provide exposure to real world projects. OdinSchool’s Data Science Course or Data Science Certification helps you master foundations of data science and even help you choose your focus area: advanced machine learning, natural language processing, or deep learning. Learn from top-rated faculty and even get career coaching sessions along the way for a holistic output.
The course offers you the opportunity to build a professional portfolio by completing 14 real-life projects, including two industry-worthy capstone projects to showcase your skills to employers. The course comes with a job guarantee and personalised 1:1 coaching. You can check out the details of the course and its curriculum in detail on our Data Science Career Track page.
