Did you know that according to Fortune Business Insights, the global data analytics market is projected to hit $349.56 billion in 2024 and could reach $924.39 billion by 2032? This massive growth means that skilled professionals in data analytics are in high demand like never before!
Taking up a data analytics course in 2024 is a brilliant move for anyone looking to have a promising career in the field of Data Analytics. From Microsoft to Google, almost every IT company is dependent on data-driven insights. Imagine how many opportunities will come your way if you have a valuable data analytics certification.
In this blog, we will discuss the Data Analytics course syllabus, skills, and tools to master in detail.
Below are the contents covered in this article:
What Is a Data Analytics Course?
The Data Analytics course is a program where you will learn how to solve complex business problems through the use of machine learning algorithms and create value out of raw data.
Data Analytics Certification will help you learn programming languages like Python and SQL, along with Power BI, one of the top business intelligence tools. You will also learn data modeling concepts like regression, clustering, and supervised and unsupervised learning. A data analytics course also teaches performance metrics, time series forecasting, and business problem-solving, providing skills for insightful storytelling.
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Data Analytics Course Syllabus
Our Data Analytics Course curriculum is designed by the instructors associated with us who are working as data analysts in companies like Amazon, Flipkart, and many more. They have structured the syllabus by keeping current industry needs in mind.
This course structure is beginner-friendly. If you are already familiar with preparatory concepts, the initial proposed modules will act as revision sessions. And thus, you will have a smooth learning experience throughout the course. Here’s the most updated syllabus for a Data Analytics course covering various subjects:
Module 1
SQL
- Introduction to SQL
- Database Normalization and Entity Relationship Model (self-paced)
- SQL Operators
- Working with SQL: Join, Tables, and Variables
- Deep Dive into SQL Functions
- Working with Subqueries
- SQL Views, Functions, and Stored Procedures
- Deep Dive into User-Defined Functions
- SQL Optimization and Performance
- Advanced Topics
- Managing Database Concurrency
- Practice Session
- Case Study
Module 2
Python
- Introduction to Python and IDEs
- Python Basics
- Data Manipulation with Numpy, Pandas, and Visualization
- Case Study
Module 3
Statistics And Probability
- Descriptive Statistics
- Probability
- Inferential Statistics
- Case Study
Module 4
Machine Learning
- Introduction to Machine Learning
- Regression
- Classification
- Clustering
- Supervised Learning
- Unsupervised Learning
- Performance Metrics
- Time Series Forecasting
Module 5
Performance Metrics
- Classification Reports – To evaluate the model on various metrics like recall, precision, f-support, etc.
- Confusion Matrix – To evaluate the true positive/negative, false positive/negative outcomes in the model. r2, adjusted r2, mean squared error, etc
Module 6
Time Series Forecasting
- Making use of Time Series Data, Gathering Insights and Useful Forecasting Solutions using Time Series Forecasting
Module 7
Business Problem Solving, Insights and Storytelling
- Business Domains
- Understanding the business problems and Formulating Hypotheses
- Exploratory Data Analysis to Gather Insights
- Data Storytelling: Narrate Stories in a Memorable Way
- Case Study
Module 8
Data Modeling
Module 9
Data Analytics Capstone Project
- Problem Statement and Project Objectives
- Approach for the Solution
- Optimum Solutions
- Evaluation Metrics
- Gathering Actionable insights
Module 10
Business Case Studies
- Customer Churn
- Sales Forecasting
- Census
- Predictive Modeling
- HR Analytics
- Dimensionality Reduction
- Housing
- Customer Segmentation
- Inventory Management
- Disease Prediction
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Skills to Master in Data Analytics
In a data analytics course, you will master statistical analysis and data visualization techniques that are essential for extracting insights from complex datasets. After learning these skills, you’ll be able to easily get business insights. The list is mentioned below:
| Hard Skills | Soft Skills |
| SQL | Collaboration |
| Data Wrangling | Communication |
| Data Analysis | Problem Solving |
| Data Visualization | Critical Thinking |
| Machine Learning | Fast Coder |
| PowerBI | Attention To Detail |
| Advanced Statistics | Work Ethics |
| Data Mining | Adaptability |
| R Programming | Continuous Learning |
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Why Is the Above Course Syllabus Preferable?
The above course syllabus is created by eminent IIT faculties and leading industry experts. They put their best collective expertise to develop the curriculum that ensures learners stay up-to-date with the latest industry trends. Designed to cater to both beginners and professionals, the syllabus guarantees proficiency in Data Analytics by the course’s conclusion. With the growing demand for Data Analytics, businesses are seeking top data professionals to gain insights and drive company growth.
So, this is the best time to gear up and start your journey with the given Data Analytics Course syllabus. With the roadmap provided, you can remain assured that you will receive excellent training that meets industry standards. Here, we are going to mention a few reasons why this course is the best fit for you!
- Data analytics skills are highly in demand across various industries, from healthcare and finance to marketing and retail.
- This course primarily focuses on machine learning, allowing for more complex analysis and predictive modeling.
- It includes current technology and trends and keeps students informed about the latest industry practices in rapidly evolving fields.
Job Opportunities After Data Analytics Certification
Getting certified in data analytics gives you vital professional skills, which make sure that you remain relevant and competitive in the IT industry. This certification provides diverse career paths and opportunities, ensuring that you get higher salaries, reflecting the high demand for skilled professionals in this rapidly evolving field.
Following are the job roles you can expect after getting certified in Data Analytics:
| Job Roles | Avg. Salary in India (per annum) | Avg. Salary in US (per annum) |
| Data Analyst | ₹8,52,000 | $77,059 |
| Data Scientist | ₹12,59,668 | $125,645 |
| Data Visualization Analyst | ₹7,20,000 | $82,640 |
| Business Analyst | ₹8,42,000 | $83,165 |
| Marketing Analyst | ₹9,20,000 | $73,780 |
| Finance Analyst | ₹13,58,309 | $91,352 |
Conclusion
In this Data Analytics Course Syllabus and Subjects blog, we referred to the most updated syllabus for you to be aware of the Data Analytics course in detail. By following this comprehensive curriculum, you’ll gain knowledge, and also, prepare yourself to attain expertise. to apply for various Data Analytics job roles: Data Analyst, Data Scientist, Business Analyst and many more. Don’t miss this opportunity to take your career forward with a future-proof skill set in Data Analytics.
Now it is evident to all of us, how data-driven insights are being used widely these days in different business sectors, and this has given IT professionals plenty of new opportunities. Don’t hesitate any longer – take the initiative to elevate your career.
FAQs
Does data analytics have a future?
As a career choice, data analytics is one of the bright choices. Nowadays, companies are highly dependent on data-driven insights, which can be fulfilled by data analytics professionals. So, having a secure career in data analytics is a very rewarding option.
Who is this course designed for?
This course is designed for beginners with no prior data experience, or is useful for working professionals who want to enhance their skill set.
What is the role of a data analyst?
A data analyst collects, processes, and analyzes data to extract insights and inform business decisions, often using statistical methods.
What are the prerequisites for this course?
Not much is needed, some courses may require basic computer literacy or familiarity with specific software, like Excel.
Does data analyst require coding?
Yes, coding is essential when you pursue a data analytics degree online. However, it does not demand highly advanced programming skills. But it is a must to master the basics of R and Python. Also, an extensive proficiency in querying languages like SQL is more than necessary.