Data Analyst Program

A data analyst's role involves collecting, cleaning, and preparing data, analyzing it to identify patterns and trends, and creating visualizations and reports to present insights effectively. They collaborate with business leaders to understand data needs and stay updated on the latest techniques. If you're intrigued by the idea of transforming raw data into actionable insights and supporting informed decision-making, this course is the perfect starting point for you.

Suitable for all backgrounds

The basic prerequisites to become a Data Analyst typically include a combination of technical skills, analytical mindset, and domain knowledge. While a technical background can be advantageous, it's not always mandatory, and individuals from non-technical backgrounds can certainly pursue a career as a data analyst. Our Data Analyst courses are designed to accommodate learners with diverse backgrounds, providing step-by-step instruction and hands-on exercises to build technical skills from scratch.

All our programs include essential add-ons focusing on soft skill development. because technical expertise alone is not enough for success in the corporate world. Our courses focus on developing essential soft skills such as effective communication, teamwork, and leadership. This comprehensive approach ensures you build the right attitude and confidence to thrive in any professional environment.

Professional Development Workshop

Comprehensive soft skills training
Interpersonal skills enhancement sessions
Professionalism and workplace etiquette modules

Communication Mastery Program

Advanced presentation techniques
Team communication strategies and collaboration methods

Placement Assisstance Services

Tailored resume writing workshops
Personal branding and LinkedIn profile optimization guidance
Interview preparations via mock interviews and assessments

Group Dynamics Training

Techniques for active and impactful participation
Strategies for effective communication and teamwork

Facilitation Skills

Gain proficiency in corporate tools like Jira, Confluence, Retrium, Mural etc
Leadership skills for effective facilitation
Facilitation techniques for fostering productive discuss

Throughout the program, students will work on hands-on projects and assignments to reinforce their learning and gain practical experience in applying data analysis techniques to real-world datasets. Additionally, they'll have access to online resources and tutorials for learning and support.

Week 1: Introduction

Course Overview and Introduction to Data Analysis
Basics of Data and Data Types
Sources and Importance of Data

Week 3: Statistical Analysis

Descriptive Statistics: Measures of Central Tendency and Dispersion
Data Distribution and Visualization
Inferential Statistics: Sampling, Hypothesis Testing, Confidence Intervals

Week 5: SQL for Data Analysis

Basics of SQL and Relational Databases
Writing Basic SQL Queries
Advanced SQL Techniques: Joins, Subqueries, Window Functions

Week 7: AI and Machine Learning

Overview of AI and Machine Learning Concepts
Supervised vs. Unsupervised Learning
Introduction to Machine Learning Libraries (scikit-learn, TensorFlow)

Week 9,10,11,12: Final Project

Apply techniques learned throughout the program to solve a real-world problem or complete a project
Develop a comprehensive project and present findings to peers and instructors

Week 2: Data Collection and Data Cleaning

Data Collection Methods and Tools
Best Practices for Data Collection
Data Cleaning and Preparation Techniques

Week 4: Data Visualization

Principles of Effective Data Visualization
Choosing the Right Type of Chart/Graph
Tools for Data Visualization (Tableau, Power BI, Excel)

Week 6: Python for Data Analysis

Python Basics: Setting up the Environment, Basic Syntax
Data Analysis with Python: Introduction to Pandas and NumPy
Basic Data Analysis Tasks with Python

Week 8: Advanced Data Analysis Techniques and Capstone Project

Data Wrangling and Cleaning with Python
Exploratory Data Analysis (EDA) with Practical Examples
Capstone Project: Defining Scope, Data Collection, Analysis, and Presentation

Q: What is the average salary of a Data Analyst in India?

The average salary for a Data Analyst in India varies based on experience, skills, and location. Entry-level data analysts can expect to earn between INR 4-8 lakhs per annum. Mid-level data analysts with a few years of experience typically earn around INR 8-12 lakhs per annum, while senior data analysts and those in lead roles can earn upwards of INR 15-20 lakhs per annum.

Q: How does the salary of a Data Analyst compare to other IT and analytics roles in India?

Data Analysts generally have competitive salaries compared to other IT and analytics roles. Their pay is comparable to that of business analysts and sometimes higher depending on the industry and specialization. Specialized skills and experience in high-demand areas can lead to higher salaries.

Q: What are the career growth opportunities for a Data Analyst in India?

Career growth opportunities for Data Analysts are extensive. They can advance to roles such as Senior Data Analyst, Data Scientist, Business Analyst, Data Engineer, or Analytics Manager. With experience, some may move into senior management positions or specialize in areas such as machine learning, big data, and business intelligence.

Q: What is the future scope of data analysis in India?

The future scope of data analysis in India is highly promising. With the increasing importance of data-driven decision-making across industries, the demand for skilled data analysts is expected to grow. Sectors such as finance, e-commerce, healthcare, and technology are heavily investing in analytics, leading to numerous job opportunities.

Q: Which industries in India are hiring Data Analysts?

Data Analysts are in demand across various industries in India, including:

Information Technology and Services
Banking and Financial Services
E-commerce and Retail
Healthcare
Telecommunications
Manufacturing
Media and Entertainment
Consulting and Professional Services

Q: What skills are essential to become a successful Data Analyst?

Essential skills for a Data Analyst include:

Proficiency in data analysis tools and software such as Microsoft Excel, SQL, R, and Python.
Knowledge of data visualization tools like Tableau, Power BI, and QlikView.
Strong analytical and problem-solving skills.
Understanding of statistical analysis and data mining techniques.
Familiarity with database management systems.
Good communication and presentation skills to convey insights effectively.

Q: How strong is the competition in the field of data analysis in India?

The competition in the field of data analysis is significant due to the growing interest in analytics and the increasing number of professionals entering this domain. However, the demand for skilled data analysts is also high, and those who continuously upgrade their skills and stay updated with the latest technologies can find ample opportunities.

Q: What educational background is preferred for a career in data analysis?

A background in computer science, statistics, mathematics, economics, or related fields is preferred. Most Data Analysts hold a Bachelor’s or Master’s degree in these areas. Additionally, relevant certifications and hands-on experience through internships or projects are highly beneficial.

A student who has completed a Data Analyst program opens up a wide range of career possibilities in various industries. Some potential career paths and entry level salary in Indian job market are:

Data Analyst

₹3.5 - ₹5 lakhs per annum

Business Analyst

₹4 to ₹6 lakhs per annum

Financial Analyst

₹4 to ₹8 lakhs per annum

Market Research Analyst

₹3 to ₹6 lakhs per annum

Healthcare Data Analyst

₹3 to ₹7 lakhs per annum

Supply Chain Analyst

₹4 to ₹8 lakhs per annum