Want to pursue a career in technology but stuck between choosing a career in machine learning and data analytics? Then, you’ve got company as this is the dilemma that numerous tech aspirants that we come across every day, are in!
Machine learning and data analytics are two terms that echo everywhere these days.Â
And why wouldn’t they? After all, every organization uses them to reap their benefits! Hence, the demand for both these skill sets is perpetually high.Â
But that’s where the challenge kicks in.Â
Choosing between two highly in-demand options is practically difficult.
Aspirants often find themselves at the crossroads where they are unable to decide whether to go for a machine learning course in Pune or data analytics courses in data Pune.
So, when in doubt, you must have a comprehensive comparison of both to make an informed choice. Here’s one to help you get going.
Comparing Machine Learning and Data Analytics – 15 Key Factors!
|
Aspect |
Machine Learning |
Data Analytics |
| Basic Purpose | Building models that enable machines to learn and make decisions with minimal human intervention. | Deriving meaningful insights from data to aid business decisions. |
| Responsibilities | Developing ML algorithms, building training models, optimizing performance and working with massive datasets. | Cleaning and analyzing data, preparing reports, dashboards and identifying patterns and trends within datasets. |
| Technical Skills | Programming (advanced level with R, Java, and Python), understanding of ML frameworks (PyTorch and TensorFlow) and solid mathematics and statistical proficiency. | Expertise in SQL, Power BI, Tableau, Excel, basic statistics and Python/R (but optional). |
| Educational Background/Eligibility | Master degree in computer science, mathematics, AI or any other related stream. | Bachelor degree in economics, business, computer science, statistics or related domains. |
| Employers | Technology companies, finance organizations, eCommerce, healthcare, pharmaceuticals, automation solutions providers, gaming companies, automobile companies, consulting firms and more. | Healthcare, BFSI, retail, eCommerce, marketing firms, advertising agencies, manufacturing companies, telecom companies, consulting firms, startups, educational organizations, and many others. |
| Learning Curve | The learning curve is considered steep, considering the profound knowledge of algorithms, high-level programming and modeling skills that the profession demands. | The learning level is often moderate and with fewer technical barriers to get started. Hence, people find it easier to begin a career as a data analyst. |
| Applications | Voice assistants, fraud detection, self-driving cars, etc. | Marketing analytics, business intelligence, supply chain analytics, financial analytics, customer segmentation, and many others – practically everywhere as every modern enterprise looks to leverage the data advantage. |
| Career Growth | High due to the rapid evolution of AI, the increasing dependence on AI/ML for decision-making, accelerating operations and ensuring accuracy. | High on account of the extensive demand across multiple industries and the need to be more data-driven in the contemporary business environment. |
| Working Style | Research-driven, and technical, involving extensive experimentation. | Collaborative and business-facing focused on actionable insights. |
| Tools and Technologies Used | Some of them include TensorFlow, Jupyter and Python. | SQL, Tableau, Excel, Powe BI, R and Python. |
| Average Salary in India (Generic figures – specific numbers may vary depending on the employer’s paying capacity, the projects available with companies, market situation, location, ML skills, experience, etc.) | The average salary range of an ML professional in India varies widely. However, it is in the range of Rs. 8-9 lakhs per annum. | The average salary of a data analyst in India is Rs. 6-7 lakhs per annum. |
| Common Positions Offered | ML engineer, AI engineer, ML research scientist, deep learning engineer, MLOps engineer and more. | Business Intelligence (BI) analyst, data analyst, reporting analyst, financial analyst, market analyst and many others. |
| Work-Life Balance | Occasionally, longer working hours on account of the complex problem-solving, model training and deployment challenges involved. | Usually, the job involves more predictable working hours, focusing in recurring reporting and analytical cycles. However, the working hours and overall work-life balance may vary based on project deadlines, pressures and the company’s culture. |
Machine Learning or Data Analytics – Who Should Choose Which Career?
Choose ML as a career if you,
- Prefer working with algorithms and building intelligent systems
- Have a solid programming background
- Love technical challenges and want to work on the latest AI advancements
- Intend to create predictive models, work on automation, and develop diverse applications
Choose data analytics as a career if you,
- Love to uncover insights from data to support business decision-making
- Like to create impactful visualizations and communicate your findings
- Want to enter a more business-centric role, influencing operational decisions
- Understand statistics and can work with SQL, Excel, Power BI, etc., comfortably
Specific career choices and decisions may differ from person to person.
Whether ML or Data Analytics – Choose Ethan’s Tech to Begin Your Career Confidently!
Both are thriving career options. However, the right guidance also matters. This is where Ethan’s Tech steps in. We offer comprehensive machine learning courses in Pune and data analytics classes in Pune. Our practical exposure and learning approach prepares you for challenges and opportunities across both these domains, unlocking the doors to remunerative career opportunities. Want to know more? Call us at +91 95133 92223.
