Learning data science or pivoting to a data career may seem daunting initially. But if you know where to start and how things fall into place. We have recently launched a comprehensive data science guide you can call your ultimate free data science 101 handbook. This Data Science 101 guide contains everything you need to become a data scientist.
What it includes:
- Importance of Data Science and Overview of the Indian Data Science job
- Core learning concepts and free resources to learn
- Key terminologies to familiarize yourself with
- Understanding data analytics and its components
- Learning data science-related subjects
- Exploring Industrial Applications of Data Science
- Acquiring essential skills and learning important tools
- Defining the ideal career path to get started
- Exploring salary insights across multiple industries
- Innovative trends that will shape the future of data science
Let’s walk through the Data Science 101 Bible.
Data Science 101 Guide: Importance and Market Overview
Data science plays a pivotal role in revolutionizing industries and transforming business decision-making. It enables extraction, analysis, and detailed interpretation of massive data sets generated, thanks to the proliferation of digital technologies. Not only this, data science empowers businesses to optimize operations and leverage the power of data to build a unique end-to-end customer experience.
As data science continues penetrating every domain and industry, the demand for skilled data scientists has skyrocketed. The lucrative career options have motivated students and professionals to learn and upskill better.
Research shows that India’s data education market is set to touch $1.39 billion by 2028 from $204.3 million in 2023. This means a compound growth of 57.5% in just five years. This comes hand-in-hand with the fact that data science jobs will grow at a similar pace.
Looking to start a career in data science? There couldn’t be a better time than now.
This is a 6-month long certification course that covers the basic concepts of data science and slowly transitions to advanced subject matters. It includes hands-on projects and assignments to ensure students acquire theoretical and practical know-how as the course progresses. If you are new to the data landscape and do not have any prior understanding of where to start, this course is perfect for you.
This course is a 1 year dedicated PG course and is more robust in curriculum, projects, and assignments. The PG course is designed for professionals with prior data knowledge and a bachelor’s degree or certification. All courses come with AnalytixLab’s signature mentor support and job search assistance. For more information on our courses, visit our course page or contact us.
Core learning concepts and free resources to learn
Data science delves into data to unearth valuable insights to drive business decisions. It’s a holistic methodology that amalgamates principles and methodologies from mathematics, statistics, artificial intelligence, and computer engineering to scrutinize extensive data sets.
This analytical process equips data scientists to pose and resolve inquiries about past events, their causation, future predictions, and the practical implications of their findings.
From predicting the weather to understanding consumer behavior, data science empowers us to make informed decisions, fuel innovation, and unlock the mysteries of our data-driven world. In essence, the magical fusion of statistics, programming, and domain expertise conjures up the future from today’s numbers.
This data science 101 guiding scripture will empower you to leverage the full potential of data. It will help you adapt to the challenges of the digital age and position yourself at the forefront of innovation and competitiveness.
Core learning concepts covered include:
- Cloud computing
- Data mining
- Data Engineering
- Predictive analytics
- Data preparation
- Understanding big data
- Data visualization
- Advanced computing
- Statistics and probability
- Core programming languages
These concepts form the foundation of data science, encompassing various tools, techniques, and methodologies necessary for efficient data analysis and utilization.
Key Terminologies to Learn
Data Science is filled with jargon and specialized terminology. The Data Science 101 guide covers important terminologies to help you navigate the complex data science landscape.
Understanding Data Analytics and its Components
Data science and Data Analytics may overlap at various junctures, but they are still two different (but related) concepts. In this comprehensive data science guide, you will learn the main differences that set the two concepts apart.
Learn how data science and data analytics differ in terms of:
- Scope
- Purpose
- Salary
- Programming tools
- Data types and more
Learning Data Science-related Subjects
Data Science is an interdisciplinary subject that branches into several core subjects worth exploring for a lucrative career. These subjects are core to understanding how data science functions across various domains and industries.
Subjects you will learn:
- Artificial Intelligence
- Machine Learning
- Deep Learning
- Natural Language Processing
- Cybersecurity
What you will get: This comprehensive data science guide comes with free reading and learning resources for each subject. Download now to get access.
Exploring Industrial Applications of Data Science
Data science isn’t limited to one sector. It is transforming industries in India and playing a major role in their success, including eCommerce, finance, healthcare, telecom, logistics, and IT.
Download the Data Science Bible to understand how data science enables each industry and how you can build a career with it.
Industries covered:
- eCommerce
- Finance
- Healthcare
- Telecom
- Logistics
- IT
Acquiring Essential Skills and Tools
Aspiring to become a data scientist is one part of the story. Learning the essential skills and tools to set you apart is a different (and important) ballgame.
The Data Science 101 guide outlines the important skills that industry experts recommend and tools that can help you make more informed data-driven decisions.
The whole section is bifurcated into categories as follows:
- Programming languages
- Big data tools
- Data manipulation and analysis tools
- Machine learning libraries
- Popular visualization libraries
- Business intelligence data science tools
Defining the Data Scientist Career Path
You can take our Data Science Bible as the Holy Grail of data landscape. This chapter outlines the ideal career path to becoming a data scientist, especially in India.
What you will learn:
- Pre-requisites of becoming a data scientist in India – Includes academic requirements, programming pre-requisites, mathematical skills, technical, and non-technical skills.
- Learning the core concepts – Outlines and pinpoints essential concepts without which your data science education is incomplete.
- Free learning resources – Lists free videos, reading materials, podcasts, books, blogs, and influencers to follow for self-paced learning.
- Project ideas – Includes project ideas for beginners, intermediate, and professionals for a tangible demonstration of your skills.
Exploring Salary Insights across Industries
After defining the career path, our guide delves into the salary insights for data scientists. You will learn salary insights across the following:
- Experience
- Industry
- Company Type
- Tools
- Job roles
- Industry
- City
For more insights into salary structure and trends for data scientists in India, download our Free Data Science Salary Survey 2023 Report.
Exploring Different Data Science Job Roles
Learning data science core concepts can help find opportunities in various job roles worth exploring. In this guide, you will learn about the programming skills, tools to learn, and technical skills you will need for each job role. Job roles included:
- Data Engineer
- AI/ML Engineer
- Database Administrator
- Data Analyst
- Business Analyst
- Data Architect
- Quantitative Analyst
What else is covered in the Data Science 101 guide?
- Career Trajectory in India
- Resume-building and Interview Guides
- Interview Enabling Coaching
- Preparation Checklists
Innovative Trends that will shape the future of Data Science
The closing chapter of our comprehensive data science 101 guide talks about the innovative trends that are playing a crucial role in shaping the future of the data landscape in India (and globally).
Conclusion
In conclusion, the future of Data Science holds immense promise and potential, poised to transform how we approach and solve complex problems in virtually every sector of our lives. As we navigate the rapidly evolving landscape of technology, data, and analytics, several key trends and considerations emerge.
The convergence of Data Science with other disciplines, such as domain expertise, social sciences, and healthcare, will continue to yield groundbreaking discoveries and solutions. Interdisciplinary collaboration will be essential in addressing complex, real-world challenges and leveraging data-driven insights to create positive societal impacts.
In brief, Data Science offers limitless potential for innovation that can reshape industries, drive discoveries, and improve lives. As we move forward, a strong commitment to ethics, inclusivity, and responsible practices will ensure that Data Science benefits society, allowing us to navigate challenges and seize opportunities to create a future that integrates data-driven progress with human values.
