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Best Data Analytics Course In Thane With Placement

100% Placement Assistance | Live Online Sessions

3 Month Personalized Live Data Analytics Training is taught by industry experts in a comprehensive & question-oriented format.

Enroll Before: 04th January, 2025

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2000+

Students Trained

100%

Placement Assistance

04 January, 2025

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7:30 AM - 9:30 AM

Lecture Timings ( IST )

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Key Highlights Of The Data Analyst Course

  • 100+ Hours Of Live Class
  • 50+ Hours of Videos
  • 1-on-1 Mentoring Sessions
  • 20+ Industry Tools Mastery
  • In-Class Live Presentations
  • 3+ Live Projects & Practice Assignments
  • 100% Placement Assistance
  • Resume & Interview Training

Get familiar with our online Data Anaylst course syllabus.

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Syllabus for Data Analyst Course

Our hybrid online Data Analyst  course is designed to teach students the basics to the advanced level concepts of Data Analyst with practice assignments and offline in-class projects which helps them to get placed in MNC’s.

Data analytics course in Thane

Term 1

In this term, you will learn how to ace Data Analytics

  • Overview of Data Analytics
  • Role of a Data Analyst
  • Introduction to Data-Driven Decision Making
  • Tools and Technologies used in Data Analysis

Term 2

In this term, you will learn how to ace Data Analytics

  • Intro to Power BI
  • Data Acquisition & Transform.
  • Modeling Basics
  • Visualization Techniques
  • Formatting & Custom Visuals 
  • Advanced DAX             
  • Power Query M Language
  • Power BI Service              
  • Data Refresh and Gateways    
  • Power BI Administration     
  • Dataflow                  
  • Paginated Reports             
  • Performance Optimization      
  • Power BI Embedded         
  • Final Project and Review 

Term 3

In this term, you will learn how to ace Data Analytics

Data Collection And Data Wrangling

  • Data Sources and Types
  • Data Collection Techniques
  • Data Cleaning and Preprocessing
    • Handling Missing Data
    • Data Transformation and Normalization
    • Outlier Detection and Treatment
  • Introduction to Data Wrangling Tools (e.g., Excel, SQL, Python)

Descriptive Statistics and Data Visualization

  • Measures of Central Tendency (Mean, Median, Mode)
  • Measures of Dispersion (Range, Variance, Standard Deviation)
  • Data Distribution (Normal, Skewness, Kurtosis)
  • Introduction to Data Visualization
    • Charts and Graphs (Bar, Pie, Line, Histogram)
    • Dashboarding (using Power BI, Tableau)

Data Visualization Best Practices

Term 4

In this term, you will learn how to ace Data Analytics

  • Excel Basics: Formulas, Functions, and Pivot Tables
  • Data Analysis Tools in Excel
  • Performing Statistical Analysis in Excel
  • Creating Data Models in Excel
  • Advanced Excel Functions (VLOOKUP, INDEX-MATCH)

Term 5

In this term, you will learn how to ace Data Analytics

  • Introduction to Databases and SQL
  • Basic SQL Queries
    • SELECT, INSERT, UPDATE, DELETE
  • SQL Joins and Subqueries
  • Data Aggregation and Grouping
  • Advanced SQL Functions (Window Functions, CTEs)
  • SQL for Data Analysis: Case Studies

  • Introduction to Python Programming
  • Python Libraries for Data Analysis (Pandas, NumPy, Matplotlib, Seaborn)
  • Data Manipulation with Pandas
    • DataFrames, Series, Indexing, and Filtering
  • Exploratory Data Analysis (EDA)
    • Descriptive Statistics, Correlation Analysis
  • Data Visualization in Python
    • Creating Visualizations with Matplotlib and Seaborn

  • Probability Theory
  • Hypothesis Testing
    • t-tests, ANOVA, Chi-Square Test
  • Regression Analysis
    • Simple Linear Regression
    • Multiple Regression
    • Logistic Regression
  • Introduction to Time Series Analysis

Term 6

In this term, you will learn how to ace Data Analytics

  • The Importance of Data Storytelling
  • Techniques for Effective Data Communication
  • Creating Reports and Dashboards
  • Presenting Data Analysis Results to Stakeholders

  • Real-World Data Analysis Project
  • Problem Identification and Data Collection
  • Data Cleaning and Analysis
  • Visualization and Reporting

Presentation of Findings

  • Building a Data Analyst Portfolio
  • Resume Writing and Interview Preparation
  • Networking and Industry Best Practices
  • Job Search Strategies and Career Pathway

0 +
HOURS OF LIVE LEARNING
0 +
Live Projects
0 +
HOURS OF VIDEO LEARNING

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Detailed Course Syllabus & Trainer List

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Join our comprehensive Data Analytics course and qualify for top industry roles, including:

Power BI Developer

  • Master the art of creating interactive dashboards and reports with Power BI.
  • Gain the skills to transform raw data into meaningful insights.
  • Become a key player in data-driven decision-making processes.

Data Analyst

  • Learn to analyze complex datasets, identify trends, and make data-driven recommendations.
  • Develop expertise in tools like Excel, SQL, and Python for effective data analysis.
  • Step into a role that is at the heart of business strategy and performance.

MIS Analyst

  • Specialize in managing and interpreting data to improve business efficiency.
  • Use tools like Excel and SQL to generate and analyze reports for management.
  • Become the go-to expert for management information systems in your organization.

Process Excellence Analyst

  • Focus on improving business processes through data analysis and optimization.
  • Gain skills in identifying process bottlenecks and recommending solutions.
  • Play a crucial role in enhancing productivity and driving organizational success.

Get More about this 

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Tools You’ll Master

Mentors

Shamli-removebg-preview
Shamli

Python Trainer
4+ Years ITExperience
4+ Years Teaching Experience

Govind Chavan
Govind Chavan

Project Trainer
5+ Years IT Experience
5+Teaching Experience

Rushikesh Deshmukh
Rushikesh Deshmukh

Digital Marketing
3+ Years IT Experience
2+Teaching Experience

Bharat
Bharat Kale

Manual Trainer
5+ Years IT Experience
5+Teaching Experience

Our Learners Work At

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Data Analytics course in Thane

Introduction to Data Analytics

Data Analytics is the process of analyzing raw data to extract valuable insights that drive decision-making. Analysts apply various techniques to identify patterns, trends, and correlations, helping organizations make data-driven decisions. As data continues to grow, mastering data analysis is crucial.

Why Data Analytics Matters

Data is generated at every touchpoint, from transactions to social media. By analyzing it, businesses can:

  • Understand Customer Behavior: Tailor products and services to customer needs.
  • Optimize Operations: Enhance efficiency and reduce costs.
  • Predict Trends: Forecast market shifts and consumer actions.

Data analysts turn raw data into insights that help drive smarter decisions.

Key Components of Data Analytics

  • Data Collection: Gathering data from diverse sources (databases, APIs).
  • Data Cleaning: Ensuring accuracy by handling inconsistencies and missing values.
  • Data Analysis: Using tools like Excel, SQL, Python, and R to uncover patterns and trends.

The Data Analytics Process

  1. Collect Data: Gather data from relevant sources.
  2. Clean and Prepare: Fix errors and format the data.
  3. Analyze: Apply statistical or machine learning techniques.
  4. Create Visualizations: Present findings through charts and graphs.
  5. Interpret and Present: Share insights to aid decision-making.

How Data Analytics Projects Are Structured

  1. Define the Problem: Identify the business challenge.
  2. Collect and Clean Data: Prepare relevant data.
  3. Conduct Analysis: Uncover insights from the data.
  4. Create Visualizations: Present results clearly.
  5. Report Findings: Share insights with stakeholders.

Role of a Data Analyst

Data analysts convert data into actionable insights using tools like Excel, SQL, Python, and visualization platforms (e.g., Tableau, Power BI). They help businesses make informed, data-driven decisions.

Applications of Data Analytics

  • Healthcare: Improve patient care and optimize resources.
  • E-commerce: Enhance pricing strategies and customer experience.
  • Finance: Detect fraud and manage investment risks.
  • Marketing: Refine campaigns and customer segmentation.

How to Get Started in Data Analytics

  • Take Courses: Learn foundational skills through platforms like Coursera or Udemy.
  • Gain Practical Experience: Work with real-world datasets.
  • Network: Join communities and seek mentorship to expand your knowledge.

Data Analytics is a vital skill for those who want to use data to make smarter, more informed decisions.

Introduction to Data Analytics

Data Analytics is the process of analyzing raw data to extract valuable insights that drive decision-making. Analysts apply various techniques to identify patterns, trends, and correlations, helping organizations make data-driven decisions. As data continues to grow, mastering data analysis is crucial.

Why Data Analytics Matters

Data is generated at every touchpoint, from transactions to social media. By analyzing it, businesses can:

  • Understand Customer Behavior: Tailor products and services to customer needs.
  • Optimize Operations: Enhance efficiency and reduce costs.
  • Predict Trends: Forecast market shifts and consumer actions.

Data analysts turn raw data into insights that help drive smarter decisions.

Key Components of Data Analytics

  • Data Collection: Gathering data from diverse sources (databases, APIs).
  • Data Cleaning: Ensuring accuracy by handling inconsistencies and missing values.
  • Data Analysis: Using tools like Excel, SQL, Python, and R to uncover patterns and trends.

The Data Analytics Process

  1. Collect Data: Gather data from relevant sources.
  2. Clean and Prepare: Fix errors and format the data.
  3. Analyze: Apply statistical or machine learning techniques.
  4. Create Visualizations: Present findings through charts and graphs.
  5. Interpret and Present: Share insights to aid decision-making.

How Data Analytics Projects Are Structured

  1. Define the Problem: Identify the business challenge.
  2. Collect and Clean Data: Prepare relevant data.
  3. Conduct Analysis: Uncover insights from the data.
  4. Create Visualizations: Present results clearly.
  5. Report Findings: Share insights with stakeholders.

Role of a Data Analyst

Data analysts convert data into actionable insights using tools like Excel, SQL, Python, and visualization platforms (e.g., Tableau, Power BI). They help businesses make informed, data-driven decisions.

Applications of Data Analytics

  • Healthcare: Improve patient care and optimize resources.
  • E-commerce: Enhance pricing strategies and customer experience.
  • Finance: Detect fraud and manage investment risks.
  • Marketing: Refine campaigns and customer segmentation.

How to Get Started in Data Analytics

  • Take Courses: Learn foundational skills through platforms like Coursera or Udemy.
  • Gain Practical Experience: Work with real-world datasets.
  • Network: Join communities and seek mentorship to expand your knowledge.

Data Analytics is a vital skill for those who want to use data to make smarter, more informed decisions.

data science course in pune

Eligibility

for Data Analyst Course​

Eligibility and Requirements for the Program

  • Graduate Background: Open to all graduates; no specific field of study required.
  • Interest in Coding: No prior coding experience needed. A willingness to learn programming languages like Python, R, and SQL is essential.
  • Time Commitment: Dedicate 3-4 hours per day for lectures, hands-on practice, and learning.
  • No Prior Experience: This program is designed for beginners, starting from the very basics.
  • Curiosity & Problem-Solving: A curious mind and an analytical approach will set you up for success.

FAQs

Frequently asked questions

What is a Data Analytics Course?

A Data Analytics course teaches you how to collect, process, and analyze data to uncover valuable insights. It covers essential skills like using analytical tools, identifying trends, and visualizing data to support business decision-making.

Do I Need a Specific Educational Background to Take a Data Analytics Course?

No specific degree is required. The course is open to anyone with a basic understanding of math and a strong willingness to learn.

What Skills Are Taught in a Data Analytics Course?

  • Excel & SQL for data manipulation and querying
  • Python/R for advanced analytics
  • Data Visualization using tools like Tableau and Power BI
  • Problem-solving & Communication skills to effectively present insights

How Long Does It Take to Complete a Data Analytics Course?

Most courses take 3-6 months to complete, depending on the pace and dedication. Accelerated programs offer faster tracks for those who want to complete the course in a shorter time.

Do I Need Coding Experience Before Starting a Data Analytics Course?

No prior coding experience is required. The course will teach Python and SQL from the basics, helping you gradually build the skills you need for data analysis.

What Tools Will I Learn in a Data Analytics Course?

In a Data Analytics course, you’ll learn to use:

  • Excel for basic data analysis
  • SQL for database querying
  • Python/R for advanced data analysis
  • Tableau/Power BI for data visualization

What Types of Industries Can Benefit from Data Analytics Skills?

Data Analytics skills are valuable across various industries:

  • Healthcare: Enhancing patient care and resource management
  • Finance: Conducting risk analysis and detecting fraud
  • E-commerce: Personalizing the customer experience
  • Marketing: Optimizing campaigns and customer segmentation

Is a Data Analytics Course Suitable for Beginners?

Yes, Data Analytics courses are designed to start with the basics and gradually introduce more advanced topics. No prior experience is needed, making it a great choice for beginners.

Will a Data Analytics Course Help Me Get a Job?

Completing a Data Analytics course equips you with valuable skills, but securing a job depends on several factors, including your practical experience, portfolio, and networking. Many courses offer career support such as resume workshops and interview coaching to increase your job prospects.

How Can I Apply the Knowledge Gained in a Data Analytics Course in Real Life?

The skills learned in a Data Analytics course can be applied to:

  • Analyze Business Performance to identify areas of improvement
  • Create Dashboards to track KPIs and business metrics
  • Identify Customer Trends to inform marketing strategies
  • Forecast Sales and optimize inventory management

What Are the Prerequisites for a Data Analytics Course?

The prerequisites for a Data Analytics course typically include:

  • Basic mathematics, particularly in statistics
  • Familiarity with Excel for data manipulation
  • Willingness to learn Python/R, which will be covered during the course

By completing a Data Analytics course, you’ll gain the essential skills needed to pursue a career in this rapidly growing field and make data-driven decisions that can have a significant impact on businesses.

How much can a data analyst earn?

Data analyst salaries vary based on factors like location, experience, and skills. In the U.S., salaries typically range from $50,000 to $80,000 per year. Experienced analysts and those with specialized skills can earn more. Salaries may differ across countries and industries.

Data Engineer

Roles and Responsibility for Data Analyst

Roles and Responsibility for Data Analyst

1. Data Collection

Gather data from diverse sources such as databases, surveys, APIs, and online platforms to ensure a comprehensive dataset for analysis.

2. Data Cleaning

Address issues like duplicates, missing values, and inaccuracies by cleaning and transforming the data into a consistent, reliable format.

3. Data Analysis

Apply statistical techniques and tools to uncover patterns, trends, and meaningful insights that can drive business decisions.

4. Data Visualization

Create visual representations like graphs, charts, and dashboards to make the findings easily understandable and actionable for stakeholders.

5. Reporting

Present your findings through detailed reports or presentations, highlighting key insights and offering recommendations to support business strategies.

6. Building Reports and Dashboards

Design and automate reports and dashboards for continuous data tracking, allowing real-time monitoring of key metrics and performance indicators.

7. Collaboration

Collaborate with cross-functional teams (such as marketing, product, and operations) to provide data-driven recommendations and support informed decision-making.

8. Data Interpretation

Translate complex data into clear, actionable insights that guide strategic decisions and improve business outcomes.

Course Duration

Data Analyst in 5 Months?

Can I Learn Data Analysis in 5 Months?

Yes, it’s absolutely possible to learn Data Analysis in 5 months with strong focus and commitment. By dedicating 3-4 hours daily to studying, practicing, and working on hands-on projects, you can develop the necessary skills. Completing real-world projects will not only reinforce your learning but also help you build a portfolio that will impress potential employers.

With consistency, a clear study plan, and a focus on practical application, you can be job-ready by the end of 5 months.

Enroll Now and get 5% Off On Course Fees

Enroll Now and get 5% Off On Course Fees

Enroll Now and get 5% Off On Course Fees

Enroll Now and get 5% Off On Course Fees