Data Analyst Course Syllabus – Fee, Duration And More

A well-structured data analyst course syllabus acts as a roadmap to help you gain essential skills in this growing field. It provides the knowledge you need to collect, clean, analyze, and present data in a way that helps discover trends, patterns, and relationships that can shape the future of industries.

With Develearn’s Data Analyst course in Mumbai, you can learn how to turn raw data into meaningful insights and drive informed business decisions. This course can help you develop the skills needed to succeed in the ever-evolving world of data. Start your journey today and become a data expert!

In this guide, we’ll explore the core elements of a data analyst course syllabus in 2024, covering the topics and tools that will set you up for success. Whether you’re new to the field or a professional looking to sharpen your skills, this breakdown will give you a clear path to mastering data analysis.

What is Data Analytics?

Data analytics is the process of studying large sets of data to find patterns, trends, and valuable insights. These insights help businesses and organizations make well-informed decisions. The process includes collecting, cleaning, analyzing, and interpreting data to discover useful information.

Data analysts use various methods and tools such as statistical analysis, data mining, and machine learning to analyze the data. In today’s world, data analytics has become crucial for businesses, allowing them to better understand their customers, improve efficiency, and discover new opportunities for growth.

Data Analyst Course Syllabus

A thoughtfully structured data analytics course provides you with the skills and knowledge necessary to draw meaningful insights from data and support informed decision-making. Below is a detailed syllabus outline for 2024, including both basic and advanced topics:

Advanced Excel Course

Duration: 60 Hours

The Advanced Excel course focuses on enhancing your Excel skills, enabling better data handling and analysis in professional settings.

Key Topics Covered:

• Data Cleaning and Preparation:
  Techniques for organizing and cleaning raw data.

• Formulas and Functions:
  Advanced formulas like VLOOKUP, INDEX-MATCH, and logical functions.

• Pivot Tables and Pivot Charts:
  Creating and customizing Pivot Tables and Charts for data analysis.

• Data Analysis Tools:
  Using Excel’s built-in tools like Goal Seek and Solver for analysis.

• Power Query:
  Importing, transforming, and merging data from different sources.

• Data Analysis with Power Pivot:
  Creating data models and using DAX formulas for complex analysis.

• Advanced Charting and Visualization:
  Building interactive charts and dashboards for better data presentation.

• Macros and VBA:
  Automating repetitive tasks with Macros and basic VBA programming.

• What-If Analysis:
  Scenario Manager and Data Tables for performing sensitivity analysis.

• Reporting and Dashboards:
  Designing dynamic reports and dashboards for professional use.

Python Course

Duration: 60 Hours

This Python course is designed specifically for data analysts, focusing on leveraging Python for data manipulation, exploration, visualization, and analysis. It equips learners with key skills and essential libraries for data-driven decision-making.

Key Topics Covered:

• Python Programming Language:
  Fundamentals of Python for data analysis.

• Data Manipulation Libraries:
  Using libraries like Pandas for handling and manipulating data.

• Data Visualization Libraries:
  Creating visualizations using Matplotlib and Seaborn.

• Jupyter Notebooks:
  Interactive coding and analysis in Jupyter environments.

• Data Cleaning and Preprocessing:
  Techniques for cleaning and preparing raw data for analysis.

• SQL Integration:
  Working with SQL databases for data retrieval and manipulation.

• Statistical Analysis:
  Applying statistical methods to analyze data.

• Data Analysis Workflow:
  Understanding the full workflow of data analysis projects.

• Web Scraping:
  Extracting data from websites using Python libraries.

• NumPy:
  Working with numerical data and arrays using NumPy.

SQL Course

Duration: 60 Hours

This SQL course provides a complete understanding of SQL, focusing on data management and querying relational databases. It’s an ideal course for beginners looking to gain essential skills in database querying and management.

Key Topics Covered:

• SQL Basics:
  Introduction to SQL, querying, and database structures.

• Data Manipulation:
  Inserting, updating, and deleting data in databases.

• Data Aggregation and Grouping:
  Using aggregate functions and grouping data for analysis.

• Data Joins and Relationships:
  Working with multiple tables using joins and relationships.

• Subqueries and Derived Tables:
  Writing subqueries and using derived tables for complex queries.

• Data Cleaning and Preparation:
  Techniques for cleaning and organizing data within SQL.

• Window Functions (Analytical Functions):
  Using window functions for advanced data analysis.

• Time Series Analysis:
  Analyzing time-based data within SQL.

• Pivoting and Unpivoting Data:
  Transforming data structures for better analysis.

• Data Visualization with SQL:
  Creating basic data visualizations directly from SQL queries.

Tableau/Power BI Course

Duration: 60 Hours

This course teaches participants how to use Tableau and Power BI to create interactive dashboards, charts, and reports, enhancing their data storytelling abilities. It focuses on data visualization tools that help data analysts turn raw data into meaningful insights, enabling clear and effective communication. By the end of the course, learners will be equipped to visualize complex information and support data-driven decision-making.

Key Topics Covered:

• Data Connection and Data Source:
  Connecting to various data sources and importing data.

• Data Transformation and Data Modeling:
  Cleaning, shaping, and modeling data for analysis.

• Data Visualization Basics:
  Understanding the principles of data visualization.

• Creating Basic Visualizations:
  Building charts, graphs, and tables for reports.

• Interactive Dashboards:
  Designing and building interactive dashboards for users.

• Advanced Visualizations:
  Creating complex visualizations like heat maps, tree maps, and scatter plots.

• Calculated Fields and Expressions:
  Writing calculated fields to customize data analysis.

• Table Calculations:
  Using table calculations for advanced analysis.

• Time Series Analysis:
  Analyzing time-based data to identify trends.

• Level of Detail (LOD) Expressions:
  Creating detailed expressions for precise data analysis.

How to Get Started as a Data Analyst

If you're looking to start a career as a data analyst, here are some key steps to guide your journey:

1. Gain a Solid Foundation:
   To kick-start your career in data analytics, it’s important to build a strong base of knowledge. Enrolling in a comprehensive program like the Data Analyst Course in Mumbai offered by DeveLearn, can provide you with the necessary skills and hands-on experience. Their course covers everything from data collection to advanced analysis techniques, making it an ideal choice for beginners and professionals looking to enhance their skills.

2. Build a Strong Portfolio:
   With the right foundation, you can begin showcasing your expertise. DeveLearn's course offers real-world projects as part of the curriculum, helping you build a portfolio that stands out to employers.

3. Network with Industry Professionals:
   Networking plays a vital role in the data industry. DeveLearn regularly connects its students with experienced data analysts and industry professionals, giving you the opportunity to learn directly from the experts.

4. Practice Data Analysis Techniques:
   Practice makes perfect, and DeveLearn ensures you have ample opportunities to work on real-world datasets, helping you apply your learning in a practical context.

5. Stay Updated with Industry Trends:
   Data analytics is constantly evolving, and DeveLearn ensures its students are always up-to-date with the latest tools and trends in the industry.

6. Learn Popular Tools:
   At DeveLearn, you’ll get hands-on training with popular data analysis tools such as Python, SQL, Excel, and Tableau, giving you an edge in the competitive job market.

Take the first step towards becoming a data analytics expert with DeveLearn's Data Analyst Course in Mumbai. Master essential tools like Python, SQL, Excel, and Tableau to turn data into valuable insights. Enroll now to start building your future in data analysis and boost your career!

Software and Tools Used in Data Analysis

A data analyst uses various software and tools to extract meaningful insights from data. These tools are not just concepts but daily essentials in real-world applications. Let’s look at some of the most common ones:

1. Microsoft Excel

Excel is one of the most widely used tools for data analysis, offering a user-friendly interface for organizing data, performing calculations, and creating visualizations. In DeveLearn’s data analyst course offline in Mumbai, you’ll learn how to use Excel’s advanced features for data cleaning, creating pivot tables, and building charts for effective reporting.

Practical Applications:

Excel is useful for tasks like budgeting, financial analysis, and reporting. In the course, you might work on projects where you clean datasets, analyze sales trends, or visualize customer data. Enrolling in DeveLearn, the best data analyst course in Mumbai, gives you hands-on experience with these tasks.

2. Python

Python is a powerful programming language known for its simplicity and extensive libraries. In DeveLearn’s course, you’ll explore Python libraries like:

• Pandas for data manipulation.

• NumPy for handling numerical data.

• Matplotlib and Seaborn for creating visualizations.

Practical Applications:

Python is widely used for data cleaning, machine learning, and statistical analysis. You may work on building recommendation systems, analyzing customer data, or forecasting trends.

3. R Programming

R is specialized in statistical computing and visualization. DeveLearn’s course covers R for tasks like data exploration, hypothesis testing, and regression analysis.

Practical Applications:

R is commonly used in research, healthcare, and finance for statistical modeling and creating publication-quality plots. You’ll apply R in real-world scenarios like analyzing survey data.

4. SQL (Structured Query Language)

SQL is the backbone of database management. In DeveLearn’s data analyst offline course in Mumbai, you’ll learn how to query databases, retrieve data, and combine tables for comprehensive analysis.

Practical Applications:

SQL is used in nearly every industry for extracting data, analyzing trends, and generating reports. You might work on projects where you analyze sales data or track web traffic in a database, gaining practical experience in this data analyst course offline in Mumbai.

5. Tableau & Power BI

Tableau and Power BI are popular tools for creating interactive dashboards and visualizations. In the course, you’ll learn how to design visually appealing dashboards to tell stories with data.

Practical Applications:

These tools are used for tracking KPIs, sales performance, and customer behavior. You’ll have the opportunity to build dashboards that visualize customer demographics or monitor website traffic.

By enrolling in DeveLearn’s Data Analyst Course in Mumbai with placement, you’ll not only learn these essential tools but also apply them to real-world projects, making you job-ready in this highly competitive field.

Conclusion

A well-rounded data analytics course syllabus is your guide to unlocking the full potential of data. It covers everything from the basics of statistics and programming to more advanced techniques like machine learning and data visualization. These skills are essential for turning raw data into valuable insights that can fuel business growth.

At DeveLearn, our Data Analyst Course in Mumbai covers key areas such as statistical analysis, data cleaning, database management with SQL, programming with Python and R, and powerful visualization tools like Tableau and Power BI. By mastering these skills, you’ll be well-prepared to tackle real-world data challenges, present findings clearly, and make a meaningful impact in your chosen field.

FAQs: Data Analyst Syllabus

Q1. What are the main subjects in a data analyst syllabus?

The syllabus typically covers business analytics and decision-making, numerical and statistical analysis, and systems analysis and design.

Q2. What are the fees for a data analyst course in Mumbai, India?

The fees for a data analyst course vary based on the program type:

• Certification level: INR 5,000–10,000

• Diploma level: INR 9,300–2,00,000

• Undergraduate level: INR 90,000–21,00,000

• Postgraduate level: INR 20,000–23,00,000

Q3. Who is eligible to become a data analyst?

To become a data analyst, a bachelor's degree in a related field such as statistics, computer science, or mathematics is typically required.

Q4. What is the basic salary of a data analyst in India?

The salary for entry-level data analysts in India typically ranges from ₹4,00,000 to ₹8,00,000 per annum, depending on skills and experience.

Q5. What is the best data analyst institute in Mumbai?

Several institutes offer quality data analyst courses in Mumbai, including DeveLearn, which provides comprehensive training with real-world projects and placement support.

Q6. What is the duration of a data analyst course in Mumbai?

The duration varies depending on the course type, ranging from 3 months for certification courses to 1-2 years for diploma or degree programs.