As the world becomes increasingly data-driven, the demand for skilled Data Analysts continues to grow. According to a report by the McKinsey Global Institute, the demand for workers with advanced digital skills, such as data analysis, is expected to grow by 55% between 2016 and 2030.
If you're interested in pursuing a career in this exciting field, enrolling in a Data Analyst Course can be a great way to get started. However, not all Data Analyst Courses are created equal, and it's important to carefully review the Data Analyst Course syllabus before making a decision.
NxtWave's Data Analyst Course Syllabus is designed by industry experts with a focus on practical experience. You will work on real-time projects to build an impressive portfolio.
What is Data Analysis?
Data analysis is the process of inspecting, cleaning, transforming, and modeling data to discover useful information, draw conclusions, and support decision-making. It involves examining data sets to identify patterns, trends, relationships, and insights that can inform business strategies, scientific research, or any field that relies on data-driven decision-making.
What Does a Data Analyst Do?
A data analyst is a professional who collects, processes and analyzes data to help organizations make informed decisions. Their role involves working with large amounts of data to identify trends, patterns, and insights that can improve business operations, strategies, and performance. Data analysts use various tools, techniques, and statistical methods to extract meaningful information from raw data.
Data Analyst Course Syllabus
Fundamentals
Static Website Design
1. Software Development Fundamentals
- Importance of Frontend
- Fundamentals
- Syntax
- Debugging
- Tweaking Code
2. HTML Basics
- HTML Elements
- HTML Headings
- HTML Paragraphs
- HTML Button
- HTML Attributes
- HTML Images
- HTML Hyperlinks
- HTML Containers
- HTML Lists
3. CSS Basics
- CSS Rulesets
- CSS Properties
- CSS Colors
- CSS Units
- CSS Box Model
- CSS Margins
- CSS Paddings
- CSS Borders
4. Bootstrap Components
Course Project
Build Tourism Website by using HTML5, CSS3, and Bootstrap.
Responsive Website Design
1. Intermediate CSS
- Block vs inline elements
- CSS Selectors
- Class Selector
- Id Selector
- Type Selector
- CSS Specificity
- CSS Inheritance
- CSS Cascading
Course Project
Build a Responsive Food Munch Website by using HTML5, CSS3, and Bootstrap.
2. Bootstrap
- Bootstrap Grid System
- Bootstrap utilities
- Display utilities
- Flex utilities
- Sizing utilities
- Spacing utilities
- Navbar
- Buttons
- Colors
Course Project
Build a Responsive eCommerce Website by using HTML5, CSS3, and Bootstrap.
Programming Foundations with Python
1. Fundamentals of Programming
- Operators, Datatypes & Variables
- Strings & Numbers
- Conditional Statements
- Loops
- String Methods
- Functions
Introduction to Databases
1. Relational Databases
- Introduction
- SQL
- Aggregation, Relationships, Join
- Querying
- ACID Properties
Data Analyst Course Syllabus PDF
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Data Analytics Specialisation
Introduction to Data Analytics
- Overview of Data Analytics
- Opportunities and Career Paths in Data Analytics
- Roles and Responsibilities of a Data Analyst
- Data Analytics Case Studies
Data Visualization
- Fundamentals of Data Visualization
- Introduction to Power BI
- Data Visualization using Power BI
Advanced-Data Visualization
- Slicers and Filters in Power BI
- Interactive Visualisations in Power BI
- Creating Paginated Reports
- Creating Dashboards in Power BI
Data Cleaning & Transformation using Excel / Power Query
- Data Cleaning Techniques
- Data Transformation Techniques
- Introduction to Power Query
- Data Types and Filters in Power Query
- Inbuilt Column and Row Transformations
- Creating a Query in Power Query
- Combining Two Data Sets
Data Modelling & DAX
- Introduction and Techniques to Data Modelling
- Creating Measures in DAX
- DAX Functions
Publishing Your Dashboards
- Introduction to Power BI Service
- Collaboration using Power BI
- Creating Dashboards using Power BI Cloud/Service
- Publishing Your Dashboard
Data Analysis using Python Libraries
- Introduction to NumPy and Pandas
- Indexing and Slicing NumPy arrays
- Indexing and Filtering Pandas data frames and series
- Modifying Pandas data frames and Series
Data Analytics using Tableau
- Fundamentals of Tableau
- Essential Design Principles for Visualization with Tableau
- Creating Dashboards and Interactive Reports in Tableau
Capstone Project
Building Captivating dashboards from different datasets across E-Commerce, Fintech, Health Tech, etc.
Frequently Asked Questions
Does Data Analyst require coding?
Yes, data analysis requires coding skills. However, it is not mandatory to have coding skills for all data analyst roles, some may focus more on data visualization, reporting, or interpreting data. Having coding skills will certainly be an advantage in the job market and can help data analysts to be more efficient and effective in their work.
How long does it take to complete a Data Analyst Course?
The duration of a Data Analyst Course can vary depending on the program and the level of instruction.
This Data Analyst Course by NxtWave is beginner friendly and takes 5 months to complete. Even a fresher can understand the technical concepts easily and create interactive dashboards from the datasets.
What is the cost of a Data Analyst Course?
The cost of NxtWave's Data Analyst Course is ₹55,000/-
It includes -
- Fundamentals and Data Analytics Training
- Fast doubt clarification from 9 AM - 9 PM Everyday
- 24/7 Online Labs to practise coding
- 10+ Real-time projects to build
- Placement Support to make you job-ready
What is the difference between a Data Analyst and a Data Scientist?
A Data Analyst focuses on examining and interpreting data to identify trends and insights that can inform business decisions. While a Data Scientist is responsible for developing and testing hypotheses, building predictive models, and using machine learning algorithms to analyse complex data sets.
What are the key topics covered in the data analyst course syllabus for 2024?
The key topics covered in the data analyst course syllabus for 2024 include:
- Introduction to Data Analytics
- Statistics for Data Analytics
- Excel for Data Analytics
- SQL for Data Analytics
- Python for Data Analytics
- Data Visualization using Tableau
- Machine Learning Fundamentals
- Data Interpretation and Communication
How to become a Data Analyst?
To become a Data Analyst, you need to build a solid foundation in various technical, analytical, and problem-solving skills. Below is a step-by-step guide based on typical course syllabi, which can help you structure your learning and career path
Final thoughts
In this data-driven world, the demand for skilled data analysts is on the rise. If you aspire to become one, it is essential to equip yourself with the right knowledge and skills.
The first step to embark on this journey is to pursue a comprehensive data analytics course which provides a strong foundation of knowledge at the outset and also includes hands-on experience through real-world projects.
NxtWave intensive 3.0 program has proven to be successful in guiding students and securing their dream job. More than 1700+ companies have hired our learners.
Don't believe our words, check out their success stories yourself.
