What is a Data Science Course and How to Pick the Best One
There’s no doubt that data science is one of the most promising career paths today. It permeates nearly every industry, shaping decisions and driving innovation. In recent years, the demand for digital skills has skyrocketed in India, and data science, interwoven with AI, stands at the forefront. A 2023 report by the Boston Consulting Group, titled “State of Data Science & AI Skills in India”, forecasts the creation of a million new jobs in this field by 2026 (1). So, what to do to become a data scientist and capitalize on this opportunity? The answer lies in a structured data science course. But what is data science course exactly, and what is in data science course? What modules/subjects does it include? Furthermore, why are they important? Let’s find out.
What to Study to Become a Data Scientist?
Procrastinating about what to study to become a data scientist? Here’s a step-by-step guide on the key academic milestones for aspirants in the field:
1. Mathematics and Computer Science
In high school, focus on subjects like mathematics and statistics, as these are essential to data science. Opting for a science stream is a strategic choice, and if possible, include computer science in your curriculum.
2. Develop Coding Skills Early
Programming languages such as Python are widely used in data science, and many educational institutions now offer Python and other coding courses tailored for students. If you have a strong interest in computers, consider enrolling in these courses during high school.
3. Pursue a Bachelor’s Degree in a Related Field
A bachelor’s degree in a relevant field—such as computer science, statistics, or mathematics—lays the groundwork for a career in data science. This degree will introduce you to fundamental concepts in programming, data structures, statistical analysis, and algorithms.
4. Consider a Master’s Degree for Specialized Knowledge
Enrolling in a Master’s program, ideally in Data Science, Computer Science, or a closely related field, enhances your profile significantly. A master’s degree demonstrates your commitment to the field and gives you deeper insights into machine learning, big data, and advanced statistical methods.
5. Pursue a Doctorate for Research-Oriented Roles
If you are inclined toward academia or research-driven roles, consider pursuing a doctoral degree in data science or a similar discipline. A PhD enables you to dive deeply into niche areas, contribute to cutting-edge research, and qualify for senior roles in academia and industry. However, be aware that a doctoral program is a demanding and time-intensive endeavor.
Data Science Courses
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What is in Data Science Course: Data Science Course Subjects
From foundational knowledge to advanced techniques, here’s what is data science course syllabus generally includes:
1. Core Concepts in Statistical Analysis and Inference
In this module, students dive deeply into statistical tools that empower them to analyze and interpret complex datasets. For instance, the module typically covers a diverse range of topics such as hypothesis testing, and Exploratory Data Analysis (EDA). Additionally, it might include statistical tests such as one-sample and paired-sample t-tests, alongside Analysis of Variance (ANOVA), and advanced topics such as Principal Component Analysis (PCA).
2. Programming and Key Software Tools
If you’re wondering what is in data science course, then programming language is an essential component. Python and C++, two of the most popular languages according to the TIOBE Index for November 2024, often become the starting point for teaching programming languages (2). Python’s flexibility and extensive libraries make it ideal for data manipulation, while R excels in statistical analysis. SQL also takes center stage, as it is essential for querying databases. Furthermore, this module might include other languages such as R, Java, Scala etc.
3. Data Cleaning and Transformation Techniques
Integral to understanding what to do to become a data scientist is knowing the significant elements that are its foundation. For instance, data cleaning and transformation is a must. Consequently, this module covers techniques for addressing issues related to cleaning and transformation, such as missing values, feature engineering to enhance predictive capabilities, and data wrangling for reformatting and organizing information. The tools for this generally includes Pandas, NumPy, and Dask among others.
4. Predictive Modeling and Machine Learning
Machine learning is increasingly becoming a pivotal part of data science. In accordance with this requirement, this module typically begins with supervised and unsupervised learning, then progresses to advanced modeling techniques like regression, classification, and clustering. By integrating frameworks such as TensorFlow, Keras, Scikit-learn, and PyTorch, students acquire the technical depth needed to create and refine machine learning models.
5. Natural Language Processing (NLP)
This module introduces students to NLP techniques, providing insight into text analysis. Here, students learn the fundamentals of text mining and sentiment analysis, exploring social media analytics to understand public opinions. Additionally, this module also covers deep semantic models for more advanced language analysis, making it essential for students looking to build their skills in interpreting textual data.
6. Database Management and Big Data Techniques
This section of the what is data science course aims to equip students with the capability to handle extensive datasets. Here, students learn to use relational databases and SQL for managing structured data. In addition, they explore big data technologies like Hadoop and Spark, which enable them to process and analyze data at a large scale.
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7. AI-Driven Business Strategies
As AI becomes more integral to business, data scientists must understand how to incorporate AI strategies into corporate frameworks. Hence, AI forms an integral part of what is data science course. In this module, students learn how to integrate AI initiatives into business strategies, addressing governance and ethics to ensure responsible AI practices. Consequently, by the end of this module, students will understand how to harness the power of AI to generate data-driven insights that are aligned with business goals.
8. Real-World Applications Through Capstone Projects
To cement a participant’s learning through practical, hands-on experience, what is a data science course often includes a capstone project that gives the students a taste of tackling real-world data challenges. Often in collaboration with industry partners, capstone projects let students work through the entire data science workflow, from data collection to model deployment.
What is Data Science Course Best for: Data Science Course Outcomes
For learners, the outcome of a data science course from a reputed institute can be classified in two ways: learning-based and career-based.
1. Outcomes in Terms of Learning
Upon completion, students of what is data science course will acquire the ability to:
- Clean, process, and analyze large datasets effectively
- Utilize data visualization tools to create compelling, interactive data stories
- Implement natural language processing for text data analysis
- Construct, test, and deploy machine learning models for predictive insights
- Integrate big data technologies for handling large-scale data
- Operate databases with SQL for effective data management
2. Outcomes in Terms of Career Progression
Completing a data science course also brings tangible career benefits, such as:
- A certificate from a recognized institution significantly strengthens your resume
- Alumni status offers networking opportunities with other data professionals
- Courses tailored for early-career professionals can kickstart a data science career, while advanced programs help mid-career professionals advance to leadership roles
What is a Data Science Course Fee?
Now that you have an understanding of what such a course could include, let’s understand what is data science course fee. The cost of these courses varies widely and is influenced by course level, duration, curriculum depth, and institution prestige. Also, programs designed for early-career entrants are generally more affordable than executive-level courses tailored for seasoned professionals. Considering all these factors, an online certificate course on data science and adjacent fields generally ranges from ₹50,000 to ₹3,50,000, whereas a Bachelor’s degree in Data Science might cost around ₹8,00,000–₹9,00,000.
However, for accurate and updated fee details, it is best to visit the course webpage, download brochures, or directly contact the institution. Since course fees are subject to change, it’s important to ensure you have the latest information before enrolling.
Are Data Science Courses Easy?
The journey to become a successful data scientist comes with its own set of challenges and hurdles. Furthermore, the learning curve can be steep at times. You need to understand that completing a data science course demands dedication, consistency, and a genuine passion for learning. It is also important to know that the field evolves rapidly. This means that courses frequently update their content to reflect the latest advancements. Therefore, success hinges on following the guidance of instructors, participating actively, practicing diligently, and keeping yourself updated. With perseverance, you will not only complete the course but also enrich your knowledge and enhance your career prospects in this lucrative field.
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Data science is an exciting field, with applications spanning artificial intelligence, business strategy, healthcare, and beyond. It’s no surprise that data scientists enjoy high demand and competitive salaries, with an average annual pay of around ₹14,00,000 per annum (3). Considering all these aspects, it’s no wonder that the Harvard Business Review called the job of data scientists as the “sexiest job of the 21st century”. (4) So, if you’re interested in such a career, looking to explore what is data science course, and eager to know exactly how and what to study to become a data scientist, consider enrolling in the data science courses offered by India’s top ranking institutions and brought to you by Emeritus. These industry-aligned programs offer the knowledge and skills to thrive in the challenging, exciting, and dynamic field of data science.
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