Data Analytics Courses In Pune

Empower your Career with the Best Data Analytics course

Comprehensive & Competitive Assessments | Qualified & Experienced Data Analytics Trainers | Focus on Practical Learning
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Fuel Your Ambition with Expert Guidance

Course Includes

Projects

Assignments

Lifetime Access

Certificate

(Course Completion)

Interview Preparation

(DSA and Soft skills training)

100% Placement Assistance

Data Analytics Course Overview

A Data Analytics Course offers a hands-on approach to mastering the art of data interpretation, focusing on real-world applications and business-driven insights. Participants dive into a variety of modules that go beyond the basics, learning not only data collection and cleaning methods but also how to harness advanced tools like Python, R, SQL, and Excel. Through case studies and interactive exercises, learners develop critical analytical thinking, transforming messy datasets into actionable business strategies.

What sets this Data Analytics Certification Course apart is its emphasis on exploratory data analysis, statistical modeling, and data visualization, ensuring that students can extract and communicate valuable insights across industries. The course also integrates industry-specific case studies, enabling participants to apply their learning in fields such as finance, healthcare, and marketing. By the end, students are not just proficient in the technical aspects but also in crafting data-driven narratives that influence decision-making processes.

Graduates are empowered to leverage data to identify patterns, optimize operations, and predict trends, positioning them as valuable assets in today’s data-centric business environment.

For those just starting out, beginner data analytics courses are specifically designed to introduce fundamental concepts and tools. These entry-level courses provide a solid foundation in data analytics, covering basic techniques and methodologies. They are ideal for individuals new to the field, offering a step-by-step approach to understanding data analysis processes. Whether available online, in-person, or through hybrid formats, these beginner courses cater to a wide range of learners and are a great starting point for anyone looking to enter the data analytics profession.

Why Start a Career in Data Analytics?

Embarking on a career through data analytics courses offers a wealth of opportunities due to the increasing reliance on data-driven decision-making across industries. As industries like finance, healthcare, technology, and marketing increasingly prioritize data-driven strategies, the need for proficient data professionals is skyrocketing. This surge is fueled by the growing importance of leveraging data to optimize decision-making, enhance customer experiences, and drive innovation across these sectors.
Data analytics certification courses provide the essential training needed to excel in this field, covering a range of topics from data collection and cleaning to more advanced techniques like data visualization and machine learning. What sets a career in data analytics apart is its versatility—the skills learned can be applied to a broad spectrum of industries and roles, offering individuals the ability to specialize in areas like business intelligence, data science, or predictive analytics.

For those just starting out, beginner data analytics courses provide an excellent foundation, introducing learners to key concepts and tools such as Excel, Python, and SQL. These courses, available in online, in-person, or hybrid formats, are ideal for anyone looking to break into the field, offering step-by-step guidance on understanding and analyzing data.

The rapid growth of the data analytics profession also ensures impressive job security and competitive salaries, making it an appealing option for those seeking long-term career stability. By pursuing data analytics certification courses, individuals not only gain valuable skills but also position themselves at the forefront of an industry that is transforming how businesses operate and compete globally.

Additionally, data analytics presents endless opportunities for ongoing learning and skill enhancement. As new technologies and data practices emerge, professionals have endless opportunities to advance their expertise and make impactful contributions to organizational success.

Who Can Do a Data Analytics Course?

A data analytics course is designed to be accessible to a diverse range of individuals, regardless of their prior experience or academic background. Beginners interested in the field can start with beginner data analytics courses that cover fundamental concepts and tools, providing a solid foundation for those new to data analysis. For professionals seeking a career change, such as those from finance, marketing, or engineering, data analytics certification courses offer specialized training to pivot into data-centric roles effectively. Additionally, students from related disciplines like computer science or statistics can enhance their skills with data analytics training to broaden their career prospects.

Professionals looking to upskill or enhance their current roles can also benefit from data analytics education. For example, business managers, marketers, and project managers can gain valuable insights into data interpretation, helping them make better decisions and improve strategies. Entrepreneurs and small business owners can leverage insights from data analytics courses to understand market trends and customer behavior, driving informed business decisions and growth. Overall, data analytics courses are tailored to accommodate various needs, equipping individuals with the knowledge and skills applicable across different sectors and job roles.

Career Opportunities for Data Analysts

A career in data analytics opens up a wide range of exciting opportunities across various industries, thanks to the increasing reliance on data-driven decision-making. Data analysts are in high demand due to their ability to transform raw data into actionable insights. Here are some key career opportunities within the field:
  1. Business Intelligence Analyst:
    • Role: Analyzes business data to provide strategic insights, often using skills learned in data analytics courses.
    • Responsibilities: Develops dashboards, performs data mining, and identifies trends and patterns.
  2. Data Scientist:
    • Role: Uses advanced analytical techniques, such as those covered in data analytics certification courses, to interpret complex datasets.
    • Responsibilities: Builds predictive models, conducts experiments, and delivers actionable insights for business strategies.
  3. Data Engineer:
    • Role: Designs, constructs, and maintains data pipelines, skills typically covered in advanced data analytics courses.
    • Responsibilities: Ensures data integrity, develops ETL processes, and manages large-scale data storage solutions.
  4. Market Research Analyst:
    • Role: Specializes in analyzing market trends and consumer behavior, applying techniques from beginner data analytics courses.
    • Responsibilities: Conducts surveys, analyzes market data, and prepares reports to guide marketing decisions.
  5. Financial Analyst:
    • Role: Analyzes financial data to support investment decisions, using skills from both basic and advanced data analytics certification courses.
    • Responsibilities: Performs financial modeling, forecasts performance, and evaluates risks.
  6. Healthcare Data Analyst:
    • Role: Analyzes healthcare data to improve patient outcomes and support research, often trained through specialized data analytics courses.
    • Responsibilities: Examines patient records, monitors healthcare trends, and helps with resource allocation.
  7. Operations Analyst:
    • Role: Enhances efficiency and reduces costs by analyzing operational data, skills that are part of data analytics certification courses.
    • Responsibilities: Identifies inefficiencies, develops improvement strategies, and supports operational planning.
  8. Product Analyst:
    • Role: Focuses on product-related data to drive development and enhance user experience, using insights gained from data analytics courses.
    • Responsibilities: Tracks product performance, analyzes customer feedback, and provides recommendations for improvements.
  9. Consultant:
    • Role: Offers expert advice on leveraging data for business improvements, often utilizing skills from various data analytics certification courses.
    • Responsibilities: Conducts data assessments, develops strategies, and advises on data-related projects.
As the demand for data-driven decision-making grows across sectors, the data analytics profession is experiencing rapid expansion, unlocking a wealth of career paths. Whether you’re just beginning your journey or seeking to elevate your expertise, data analytics courses and certification programs serve as essential stepping stones, equipping you with cutting-edge skills that are in high demand. What makes these programs truly valuable is their ability to not only teach the technical aspects—like mastering data visualization, machine learning, and predictive analytics—but also to shape a strategic mindset for interpreting data to drive business results. These courses provide hands-on experience, leveraging industry-standard tools like Python, SQL, and Tableau, and prepare you for specialized roles such as data analyst, business intelligence expert, or data scientist. By enrolling in these courses, you gain the flexibility to pursue various roles across industries, including healthcare, finance, e-commerce, and technology, where data is integral to innovation and operational efficiency. The field continues to evolve, and those equipped with up-to-date skills are poised to become valuable contributors to the data analytics revolution that is transforming the modern business landscape.

Why Choose a Data Analytics Course from ITView?

Choosing a data analytics course at ITView gives you the advantage of mastering industry-leading tools and technologies, making you a well-rounded professional ready for today’s data-driven world. Our comprehensive curriculum goes beyond just theory, offering hands-on training with powerful tools like Tableau, Power BI, Advanced Excel, and Python programming. These tools are essential for tasks like data visualization, statistical analysis, and automating data processes, giving you a competitive edge in the job market.

In addition to technical expertise, our course emphasizes real-world applications through case studies that mirror the challenges faced by businesses today. You’ll gain practical experience in using Tableau and Power BI to create dynamic dashboards, leverage Advanced Excel for in-depth data analysis, and develop coding skills with Python to automate complex data workflows.

But ITView goes further by supporting your career development. We offer soft skills training to refine your communication, teamwork, and problem-solving abilities. Our career services, including resume building, mock interviews, and proactive placement assistance, ensure you’re prepared to secure your desired role.

Confused about how to get a job? Start a career in data analytics. Contact us for detailed insights and get started today!

Data Analytics Certification Course Outline

Duration : 6 months

Sessions :

  • Weekdays – 4 per week
  • Weekends – 2 per week

Prerequisites :

  • There is no such Prerequisites for this course.
  • Basic computer knowledge will be advantage.
Topics: 

Database

Python

Advanced Excel

Tableau

PowerBI

Data Analytics Course Curriculum

MySQL Database (SQL)
  • What is Data
  • What is databases
  • What is RDBMS
  • Advantages of RDBMS
  • Why RDBMS
  • Users present in Database
  • What is SQL
  • Installing MYSQL
  • Set up MYSQL Workbench Tool
  • CREATE database, table
  • Data types in SQL
  • ALTER commands
  • RENAME table
  • DROP ,Truncate commands
  • Comments in SQL
  • Insert records in table
  • Update the table records
  • Delete the records from table
  • Managing the record in table
  • PRIMARY KEY constraints
  • FOREIGN KEY constraints
  • NOT NULL constraints
  • UNIQUE constraints
  • CHECK constraints
  • DEFAULT
  • Autoincrement
  • Row Restriction WHERE clause
  • Comparison Operators
  • Logical Operators
  • SQL Operators-LIKE IN NOT NULL
  • DISTINCT
  • ORDER BY
  • Literals Concatenation
  • What is a group function
  • MIN MAX
  • AVG SUM
  • COUNT
  • GROUP BY clause
  • HAVING clause
  • What is a Join
  • Types of joins
  • INNER JOIN
  • LEFT JOIN
  • RIGHT JOIN
  • SELF JOIN
  • What is subquery
  • Types of subquery
  • Single row subquery
  • Multiple row subquery
  • Corelated subquery
  • ALL ANY Operators
  • What is Trigger
  • Write a trigger in SQL
  • Usage of Trigger
  • Read excel data in SQL
Python Programming
  • Why Python where to use it?
  • Features of Python
  • Domains where Python is used
  • Python environment Setup
  • Discuss about IDE’s like IDLE, Pycharm
  • How to work in an interactive shell.
  • Identifiers, Keywords in Python
  • Operators in Python
  • Standard Project Set up
  • Variables and Data Types
  • Debugging Python Programs using debugger in Pycharm/pdb
  • Taking User Input
  • Decision or Conditional Statements
  • Repeating or Looping Statements and Nested Statements
  • break, continue and pass statements
  • List with indexing slicing and its behavior
  • Tuples its accessing and functions
  • Strings accessing and its methods
  • Set with only unique data and manipulation
  • Dictionary and its functionalities
  • How to create a Python function
  • Return type functions
  • Function with Parameters/Arguments
    • Required/Positional arguments
    • Keyword/Named Arguments
    • Default Arguments
  • Variable -length arguments
  • Anonymous/Lambda functions
  • Map() ,filter() and reduce()
  • Iterators and Decorators
  • What is a class, Structure of a class,
  • Creating Object and Accessing the behavior ,attributes
  • Constructors in Python
  • Inheritance and its types
  • Polymorphism-Overriding
  • Abstraction Implementation Hiding
  • Encapsulation data hiding
  • What is an Exceptions
  • How to handle exceptions
  • using try….except…else
  • Try-finally clause
  • Python Standard Exceptions
  • Create Custom exception/user defined
  • Exceptions raise keyword
  • What is a module in Python
  • How to access built in Libraries
  • Built in Libraries Math/Random Modules
  • Describe Packages and directories
  • How to import various modules from import statements
  • When to use packages and directories
  • Date and Time modules
  • What are Regular Expressions
  • The match and search Function
  • Search and Replace feature using RE
  • Meta characters with each symbols
  • Create a Set for valid regular expression
  • What is Multi Tasking?
  • What is a thread?
  • Thread Life cycle
  • Creation of Thread in Python
  • Start a thread
  • Using Threading Module
  • When to use files?
  • Create files in Python
  • Different file modes for reading, writing ,appending
  • os modules for various functions
  • Remove and rename a file
  • Create directories and sub directories
  • Current directory mode /remove directories
  • Python MySQL Database Access
  • Create Database Connection
  • DML and DDL Operations with Databases
  • Performing Transactions
  • Handling Database Errors
  • Disconnecting Database
Advance Excel
  • What is Excel and use Excel
  • Excel Ranges ,Selection of Ranges
  • Conditional Statements
  • Operators-Relational and Logical
  • Pivoting the data
  • Dynamic Array Formuales
  • Time and date functions
  • Formula based formatting
  • Lookup and reference Functions
  • Counting Rows and Columns
  • Joining data with VLOOKUP
  • Selecting List of Items with CHOOSE
  • Common Excel Statistical Functions
  • Counting Rows and Columns
  • Excel Data Analysis-Data Visualization
  • Visualizing Data with Charts
  • Charts Elements and Chart Styles
  • Data Labels
  • Quick Layout
Tableau
  1. Buisness Intelligience Overview
    • Introduction to Tableau
    • Product Components
    • Architecture
    • Need of Data Visualization
    • Data Connectors
    • Data Model
    • File Types
    • Dimensions & Measures
    • Show Me
    • Installing Tableau
    • Different Tableau versions and pricing
    • Look and feel of dashboards created in Tableau
    • Joins Supported in Tableau.
  2. Hierarchy
    • Worksheet Options
    • File Types
    • Heap Map
    • Tree Map
    • Highlight table
    • Symbol Map
    • Filled Map
    • Scatter Plot
  3. Data Source Filters
    • User Filter overview
    • Parameters
    • Groups
    • Sets Basic.
  4. Constant Sets
    • Computed Sets
    • IN Members-Out Members
    • Combined Sets
    • Aggregated& non Aggregated Values
    • Adhoc Calculations
    • Types of Calculations (Basic, Table, LOD)
    • Calculated Fields
    • ZN Function
    • How to find No of occurrence of letters?
  5. Date Functions
    • How to find no of days to ship?
    • how to find month
    • Type Conversions
    • Logical Functions
    • IIF Function
    • User Functions
  6. Table Calculations
    • First()
    • Last()
    • Index()
    • Rank()
    • Rank Dense()
    • Rank Modified
    • Rank Percentile
    • Rank Unique
    • Running Average
    • Windows Functions
    • Conditional Colouring using windows functions
    • Difference between Normal Aggregation & Windows Aggregations
    • Quick Table Calculations – Compute Using Table Across-Pane Across Etc.
    • Calculation Assistance
  7. Table Functions
    • Running Total Difference
    • Percentage Difference
    • Percent of Total Percentile
    • Moving Average
    • YTD Total
    • Compound growth Rate
    • Rank Methods- “Competition, Modified Competition, Dense”
    • LOD Calculations-Fixed LOD
    • Include LOD
    • Exclude LOD with examples
    • Include
    • Exclude LOD
    • What is specified dimension & what is view, dimension
  8. Page Shelf
    • Analytics Window
    • Constant Line
    • Average Line
    • Median with quartiles & Totals
    • Model (Average with 95% CI, median with 95%, quartile, cluster)
    • Custom (Reference Line, Reference Band, Distribution, Band) with examples
    • Confidence Interval (CI)
    • Clusters
    • K-Means
    • Clustering
  9. Forecasting
    • 4 Factors of forecasting (Trend, Seasonality, Cyclic Fluctuations, Residues/Noise)
    • Forecast Options
    • Forecast Models
    • Additive
    • Multiplicative
    • Quality
    • Trend Line
    • Types (Linear, Exponential, Logarithmic, Polynomial) Options(Linear, Exponential, Logarithmic, Polynomial Degree)
    • Box plot
    • Dashboards
    • Purpose of Dashboard
    • Actions
    • Highlights
    • Action URL
    • Select
    • Hover
    • Menu in Actions with examples
  10. Device Preview
    • Layout manager
    • Layout Objects
    • Horizontal Vertical
    • Objects
    • text
    • Images Fixed and floating sheets Story
    • Caption number dots, etc..
  11. Data Blending
    • Data Blending Example
    • Cross-Database Joins
    • Data Extracts
  12. API Integration with tableau
    • Javascript from embdedded Analytics Using
  13. Maps using groups
    • Dual axis maps
    • YTD MTD QTD Calculations
    • How to calculate Last Year Sales
    • Current Year Sales
    • Current Year Sales
  14. Advanced Visualization
    • Gant Chart Histogram
    • Funnel Chart Traditional
    • funnel chart Bump Chart
    • Waterfall Chart Control Chart.
  15. . Tableau Online
    • User Interface
    • Publishing Workbooks
    • Data Sources
    • Scheduling
    • Extract Refresh
    • Creating Projects
    • Creating Groups
    • Users Assigning Permissions to users
    • Subscriptions of reports.
  16. Tableau Online User Filter
    • DataSource Filters
  17. PROJECT
    • Dashboards
Power BI
  1. Introduction To Power BI
    • Introduction to Data warehouse
    • Data warehouse Tools
    • What is Power BI?
    • Power BI – Flow of Activity
    • Building Blocks of Power BI
    • Power BI – Primary Tools : Power Pivot, Power Query, Power View, Power Map, Power Q&A, Power BI Desktop
  2. PowerBI Desktop
    • Power BI Desktop – Install
    • Data Sources and Connections
    • Connect to Data in Power BI Desktop
    • How to use Query Editor in Power BI
    • Advanced Data changes and transformation
    • Views in Power BI Desktop
    • Modeling Data – Manage Data Relationship, Create Calculated Columns, Optimize Data Models
  3. DataAnalysis Expressions (DAX)
    • What is DAX?
    • Data Types in DAX
    • Calculation Types
    • DAX Functions : Date and Time, Time Intelligence, Information, Logical, Mathematical, Statistical, Text, Aggregate Measures in DAX
    • Table Relationships and DAX
  4. Data Visualization
    • Why Data Visualization
    • Practices for Data Visualization
    • Reports in Power BI
    • Charts in Power BI (Scatter, Waterfall, Funnel)
    • Slicers
    • Map Visualizations
    • Gauges and Single Number Cards
  5. Custom Visualization
    • What Are Custom Visuals?
    • Office Store
    • Downloading Custom Visuals
    • Importing Custom Visuals in Power BI Report
    • KPI Visuals
    • Data Binding in Power BI
  6. Power BI Integration page and Integration
    • Data Gateways
    • Content packs
    • Power BI Report Server
  7. Power BI Embedded
    • Power BI Embedded Conceptual Model
    • Workspace Collection
    • Dashboard vs Reports
    • Creating a Dashboard
    • Dashboard Tiles
    • Pinning Tiles
    • Quick Insights with Power BI
    • Power BI Publisher for Excel
  8. Power BI Q&A
    • Power BI Q&A
    • Dashboard
  9. Project
    • Project Implementation
    • Presentation on Projects
Soft Skills
  1. Introduction to Soft Skills
    • Communication Skills
    • Presentation Skills
    • Time Management
    • Body Language & Etiquettes
    • Group Discussions & Interview Skills
    • Preparation of CV
    • Interview
  2. Intelligence Skills
    • Emotional Intelligence Skills
    • Life Skills
    • Presentation on Soft Skills
    • Body Language & Etiquettes
    • Group Discussions & Interview Skills
  3. Personality Development
    • What is personality
    • Types of personality
    • Elements of personality development
    • Goal Settings
    • Creativity
    • Human Values
    • Stress Management
  4. Workplace Etiquette
    • Behavior at work
    • Personal etiquette
    • Using office utilities and resources
    • Postures
    • Gestures
    • Eye contact
  5. Self Discovery
    • Know yourself
    • SWOT – Strength, Weakness, Opportunities, Threats
  6. Communication
    • Verbal Language
    • Written Communication
    • Speech Clarity
    • Modulation of Voice(Tone, Pitch)
    • Listening Skills

Reviews

Rohan Pandit

Rohan Pandit

I have done my Full stack Python and Data Analytics courses from ITView, Been stuck at senior level for so long, after up skilling from ITview’s advanced Industry specific courses I’ve been offered multiple Team Leader positions, currently working as team lead at Infosys, Pune. Thanks to Nirali and Abhijeet for friend like guidance and reference! I’ll joining you guys for next AWS boot camp soon.
Raj Bhanushali

Raj Bhanushali

Absolutely stellar experience at IT View Inspired Learning! Their data analytics and full stack developer courses are top-notch, providing comprehensive training that's both engaging and practical. The instructors are experts in their field, delivering content with clarity and enthusiasm. The hands-on projects were invaluable for honing my skills, and the supportive learning environment fostered collaboration among classmates. Highly recommend IT View Inspired Learning for anyone looking to excel in data analytics and full stack development!
Janvi Davda

Janvi Davda

The data analytics course at ITView was an enriching experience. The instructors were not only highly knowledgeable but also made the learning process engaging and interactive. The course content was well-structured and comprehensive, covering essential concepts and tools like PowerBI and Tableau in data analytics. Overall, it equipped me with practical skills and insights that I can readily apply in various real-world scenarios. Thank you Krishna Mam, Nirali Mam and Abhijeet Sir.

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