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Gain practical skills in data analysis and AI with expert-led Data Analytics Course in Bhopal.
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4.5/5Course Duration
80 Hrs.Live Project
3 ProjectCertification Pass
GuaranteedTraining Format
Live Online /Self-Paced/ClassroomWatch Live Classes
Speciality
200+
Professionals Trained
3+
Batches every month
20+
Countries & Counting
100+
Corporate Served- With this period of the digital economy, organizations produce a large volume of structured and unstructured data that require analysis by specialists to enable them to make well-informed decisions. Data Analytics Course In Bhopal has core skills like Python programming, SQL query, statistical modeling, data visualization, and machine learning basics. Preparing for this course in Bhopal enables the students to work on live projects and software of industry applications, so they will not be afraid to step into the data-driven job sector.
Data Analytics Course In Bhopal
- The primary goal of this course is to get the students ready for work by sharpening their data analytics basics and problem-solving skills in real scenarios. Data Analysis Training In Bhopal lays emphasis on practical application with tools such as Python, Excel, Power BI, Tableau, and R. Along with this, the students study advanced methods such as predictive modeling, data mining, and big data management with Hadoop or Spark. The Bhopal program also equips students with international certifications that offer greater career prospects. The learners can clean data, conclude, and present results at the end.
Learning statistics and mathematics concepts for analytics
Acquiring hands-on skills in Python, R, SQL, and Excel
Acquiring visualization tools such as Power BI and Tableau
Mastery of data cleaning, preprocessing, and transformation
Model building for predictive and prescriptive analytics
Application of analytical tools to solve case studies and projects
- There are some special features in the course that have made the course popular among students as well as working professionals. The course is designed according to industry needs, with foundation and advanced levels. Students are given access to live classes, recorded classes, and doubt clearance classes. One of the unique aspects of Data Analytics Course Online is the focus on experiential learning by means of practice assignments and projects. The students are also provided with resume writing, placement, and interview coaching. Hands-on skills are developed through an exposure to industrial case studies in finance, healthcare, and e-commerce.
Industry-approved curriculum with practical approach
Live industrial case studies and projects in diversified sectors
Flexible learning: offline classes and online classes are both available
Exclusive interview and placement classes
Periodic tests and expert doubt-clearing sessions
Guidance for international certifications such as Microsoft, Google, or SAS
- Eligibility criteria of this course are relaxed, hence the course is available for working professionals as well as fresh graduates. Students from computer science, mathematics, engineering, economics, or commerce background are free to join without any problem. It is also pursued by professionals currently engaged in IT, finance, business analysis, or operations as it enhances their skills.
- There is no need for any programming skills, but a basic understanding of logic and mathematics proves to be useful. Data Analyst Classes In Bhopal is a beginner's course but then progresses to expert levels for working professionals looking for professional enhancement.
- Who can take admission for this course:
Freshers looking to build a career in data analytics
IT professionals who would like to switch careers to analytics positions
Business analysts in order to leverage newer data tools
Accountants, HR professionals, and marketing professionals who deal with data on a daily basis
Students looking to prepare for advanced courses on analytics or AI
- The future of data analytics is massive as companies around the world are dependent on data-driven decisions. Completing this course in Bhopal opens up opportunities in IT firms, finance institutions, e-commerce, healthcare, and manufacturing industries. Companies require competent data analysts to aid in strategic decision-making as automation and artificial intelligence are picking up pace. Data Analysis Course In Bhopal does not only prepare one for internal positions in Bhopal but also national and international positions. With the global market turning towards digitalization, the scope of professionals in analytics increases.
IT, banking, and consulting careers
Scope in multinational companies and start-ups
Scope to transition to higher areas such as data science or AI
Very high demand in industries such as healthcare, retail, and logistics
- This course is designed in specially crafted modules to learn step by step. All the modules, from Excel-based basic analytics to statistical modeling advanced, are taught. It begins with the introductory analytics and then progresses through tools such as SQL, Python, and Tableau. The advanced modules include machine learning, big data handling, and cloud analytics. Assignments, quizzes, and projects are taught in every module to learn by doing.
Introduction to Business Intelligence and Data Analytics
Excel for Data Cleaning Techniques and Analytics
SQL and Database Management
Python/R Programming for Analytics
Data Visualization with Power BI and Tableau
Statistics and Probability for Data Analytics
Predictive Modeling and Machine Learning Basics
Big Data with Hadoop and Spark
Capstone Project and Case Studies
- Certifications are an indication of one's skills and expand professional prospects. Students can attempt globally accepted certifications that are extremely in demand from the corporate world after taking Data Analytics Institute In Bhopal. Certain certifications are included in the course, while others need preparation, for which suggestions are given. These certifications enhance your reliability and make your profile inviting to recruiters in India and worldwide.
- Freshers who attend Data Analytics Institute In Bhopal are likely to get reasonable salary packages based on their skill set and company. Average freshers get INR 3.5 to 6 LPA in India. Depending on the experience and qualifications of the project, students can hope for better offers. Being an emerging IT and education hub, Bhopal offers more scope, with work-from-home culture escalating too. The salary increases as the experience grows, much faster than in most other sectors, with mid-level professionals crossing 10 to 15 LPA within two years.
Technical skill level and project experience
Qualifications pursued along with the course
Type of firm: startup, MNC, or consulting firm
Specialization in domain: finance, retail, healthcare, etc.
- Career advancement in this field is gigantic and full of possibilities. The students may begin as data analysts and then gradually advance to become business intelligence experts, data scientists, or AI engineers in the coming years. As they gain experience, they can move on to become data consultants or team leads for handling analytics projects. Data Analytics Training Institute in Bhopal does not provide only the junior-level roles but a career development line for the long term as well. Organizations across the globe are investing in analytics that provide job security as well as career progression.
Data Analyst Business Analyst Data Scientist
Analytics Engineer BI Specialist Project Lead
Consultant Manager Head of Analytics
- It is the most sought-after course provided in Bhopal because it is heavily demanded by industries and has a hands-on training strategy. It is a favorite course among the students because it connects industry and academics. The course is also my favorite as it is about developing using recent tools such as Python, Power BI, and Tableau that are used directly by companies. With the placements and certification provided, Data Analytics Training In Bhopal offers all that a student needs to change or begin a career.
Healthy demand for data analytics professionals in India and worldwide
Affordable and simple training in Bhopal
Practical projects are available in the course
Certifications and placement services are offered
Includes beginner and advanced level
- Completion of Data Analytics Classes In Bhopal provides entry to numerous career positions. A data analyst processes, cleans, and collects data to create reports and dashboards. Business analysts see the potential in bridging data insights to decision-making. Data visualization specialists craft considerate charts and dashboards with tools such as Tableau. Students may possess data scientist positions with further studies.
Data Analyst
Business Analyst
Data Scientist (entry level)
BI Developer
SQL Analyst
Reporting Specialist
- After the completion of this course, the professionals are placed in data-driven industries. Finance, healthcare, e-commerce, IT, and consulting firms hire analytics professionals on a regular basis. Government departments and research departments in Bhopal and other cities employ data analysts. Because of digitalization, almost every industry needs analytical support.
IT and Software Companies
Banking and Financial Institutions
Healthcare and Pharmaceutical Companies
E-commerce and Retail Businesses
Manufacturing and Supply Chain
Government Data Projects
Research and Education Institutes
- We are the best institution to take this course because we provide a well-designed curriculum, hands-on training policy, and good placement support.
- Our course is different from others in the sense that it is entirely focused on work with live projects, industry expert mentoring, and newer tools. Individual career counseling, mock interviews, and certification assistance are also provided by us. Bhopal candidates opt for our course as we cater to technical as well as career development dimensions, making it a whole package for data analytics success. Why choose us:
New and industry-focused course material
Trained faculties with practical industry project experience
Learning through case studies with practical orientation
Placement support through top recruitment agencies
Low fee of the course with flexible learning programs
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CURRICULUM & PROJECTS
Data Analytics Training Program
- Introduction
- What is Data Analytic
- Common Terms in Data Analytics
- What is data
- Classication of data
- Relevance in industry and need of the hour
- Types of problems and business objectives in various industries
- How leading companies are harnessing the power of analytics
- Critical success drivers.
- Overview of Data Analytics tools & their popularity.
- Data Analytics Methodology & problem-solving framework.
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- Understanding Concepts of Excel
- Creation of Excel Sheet Data
- Range Name, Format Painter
- Conditional Formatting, Wrap Text, Merge & Centre
- Sort, Filter, Advance Filter
- Different type of Chart Creations
- Auditing, (Trace Precedents, Trace Dependents)Print Area
- Data Validations, Consolidate, Subtotal
- What if Analysis (Data Table, Goal Seek, Scenario)
- Solver, Freeze Panes
- Various Simple Functions in Excel(Sum, Average, Max, Min)
- Real Life Assignment work
- Ms Excel Advance
- Advance Data Sorting
- Multi-level sorting
- Restoring data to original order after performing sorting
- Sort by icons
- Sort by colours
- Lookup Functions
- Subtotal, Multi-Level Subtotal
- Grouping Features
- Consolidation With Several Worksheets
- Filter
- Printing of Raw & Column Heading on Each Page
- Workbook Protection and Worksheet Protection
- Specified Range Protection in Worksheet
- Excel Data Analysis
- Data Table
- Pivot Table
- Generating MIS Report In Excel
- Text Functions
- Lookup & Reference Function
- Logical Functions & Date and Time Functions
- Database Functions
- Statistical Functions
- Financial Functions
- Functions for Calculation Depreciation
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- SQL Server Fundamentals
- SQL Server 2019 Installation
- Service Accounts & Use, Authentication Modes & Usage, Instance Congurations
- SQL Server Features & Purpose
- Using Management Studio (SSMS)
- Conguration Tools & SQLCMD
- Conventions & Collation
- SQL Server 2019 Database Design
- SQL Database Architecture
- Database Creation using GUI
- Database Creation using T-SQL scripts
- DB Design using Files and File Groups
- File locations and Size parameters
- Database Structure modications
- SQL Tables in MS SQL Server
- SQL Server Database Tables
- Table creation using T-SQL Scripts
- Naming Conventions for Columns
- Single Row and Multi-Row Inserts
- Table Aliases
- Column Aliases & Usage
- Table creation using Schemas
- Basic INSERT
- UPDATE
- DELETE
- SELECT queries and Schemas
- Use of WHERE, IN and BETWEEN
- Variants of SELECT statement
- ORDER BY
- GROUPING
- HAVING
- ROWCOUNT and CUBE Functions
- Data Validation and Constraints
- Table creation using Constraints
- NULL and IDENTITY properties
- UNIQUE KEY Constraint and NOT NULL
- PRIMARY KEY Constraint & Usage
- CHECK and DEFAULT Constraints
- Naming Composite Primary Keys
- Disabling Constraints & Other Options
- Views and Row Data Security
- Benets of Views in SQL Database
- Views on Tables and Views
- SCHEMA BINDING and ENCRYPTION
- Issues with Views and ALTER TABLE
- Common System Views and Metadata
- Common Dynamic Management views
- Working with JOINS inside views
- Indexes and Query tuning
- Need for Indexes & Usage
- Indexing Table & View Columns
- Index SCAN and SEEK
- INCLUDED Indexes & Usage
- Materializing Views (storage level)
- Composite Indexed Columns & Keys
- Indexes and Table Constraints
- Primary Keys & Non-Clustered Indexes
- Stored Procedures and Benets
- Why to use Stored Procedures
- Types of Stored Procedures
- Use of Variables and parameters
- SCHEMABINDING and ENCRYPTION
- INPUT and OUTPUT parameters
- System level Stored Procedures
- Dynamic SQL and parameterization
- System functions and Usage
- Scalar Valued Functions
- Types of Table Valued Functions
- SCHEMABINDING and ENCRYPTION
- System Functions and usage
- Date Functions
- Time Functions
- String and Operational Functions
- ROW_COUNT
- GROUPING Functions
- Triggers, cursors, memory limitations
- Why to use Triggers
- DML Triggers and Performance impact
- INSERTED and DELETED memory tables
- Data Audit operations & Sampling
- Database Triggers and Server Triggers
- Bulk Operations with Triggers
- Cursors and Memory Limitations
- Cursor declaration and Life cycle
- STATIC
- DYNAMIC
- SCROLL Cursors
- FORWARD_ONLY and LOCAL Cursors
- KEYSET Cursors with Complex SPs
- Transactions Management
- ACID Properties and Scope
- EXPLICIT Transaction types
- IMPLICIT Transactions and options
- AUTOCOMMIT Transaction and usage
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- Introduction to Power BI
- Overview of BI concepts
- Why we need BI
- Introduction to SSBI
- SSBI Tools
- Why Power BI
- What is Power BI
- Building Blocks of Power BI
- Getting started with Power BI Desktop
- Get Power BI Tools
- Introduction to Tools and Terminology
- Dashboard in Minutes
- Interacting with your Dashboards
- Sharing Dashboards and Reports
- Power BI Desktop
- Power BI Desktop
- Extracting data from various sources
- Workspaces in Power BI
- Power BI Data Transformation
- Data Transformation
- Query Editor
- Connecting Power BI Desktop to our Data Sources
- Editing Rows
- Understanding Append Queries
- Editing Columns
- Replacing Values
- Formatting Data
- Pivoting and Unpivoting Columns
- Splitting Columns
- Creating a New Group for our Queries
- Introducing the Star Schema
- Duplicating and Referencing Queries
- Creating the Dimension Tables
- Entering Data Manually
- Merging Queries
- Finishing the Dimension Table
- Introducing the another DimensionTable
- Creating an Index Column
- Duplicating Columns and Extracting Information
- Creating Conditional Columns
- Creating the FACT Table
- Performing Basic Mathematical Operations
- Improving Performance and Loading Data into the Data Model
- Modelling with Power BI
- Introduction to Modelling
- Modelling Data
- Manage Data Relationship
- Optimize Data Models
- Cardinality and Cross Filtering
- Default Summarization & Sort by
- Creating Calculated Columns
- Creating Measures & Quick Measures
- Data Analysis Expressions (DAX)
- What is DAX
- Data Types in DAX
- Calculation Types
- Syntax, Functions, Context Options
- DAX Functions
- Measures in DAX
- Measures and Calculated Columns
- ROW Context and Filter Context in DAX
- Operators in DAX - Real-time Usage
- Quick Measures in DAX - Auto validations
- In-Memory Processing DAX Performance
- Power BI Desktop Visualisations
- How to use Visual in Power BI
- What Are Custom Visuals
- Creating Visualisations and Colour Formatting
- Setting Sort Order
- Scatter & Bubble Charts & Play Axis
- Tooltips and Slicers, Timeline Slicers & Sync Slicers
- Cross Filtering and Highlighting
- Visual, Page and Report Level Filters
- Drill Down/Up
- Hierarchies and Reference/Constant Lines
- Tables, Matrices & Conditional Formatting
- KPI's, Cards & Gauges
- Map Visualizations
- Custom Visuals
- Managing and Arranging
- Drill through and Custom Report Themes
- Grouping and Binning and Selection Pane, Bookmarks & Buttons
- Data Binding and Power BI Report Server
- Introduction to Power BI Dashboard and Data Insights
- Why Dashboard and Dashboard vs Reports
- Creating Dashboards
- Conguring a Dashboard Dashboard Tiles, Pinning Tiles
- Power BI Q&A
- Quick Insights in Power BI
- Direct Connectivity
- Custom Data Gateways
- Exploring live connections to data with Power BI
- Connecting directly to SQL Server
- Connectivity with CSV & Text Files
- Excel with Power BI Connect Excel to Power BI, Power BI Publisher for Excel
- Content packs
- Update content packs
- Publishing and Sharing
- Introduction and Sharing Options Overview
- Publish from Power BI Desktop and Publish to Web
- Share Dashboard with Power BI Service
- Workspaces (Power BI Pro) and Content Packs (Power BI Pro)
- Print or Save as PDF and Row Level Security (Power BI Pro)
- Export Data from a Visualization
- Export to PowerPoint and Sharing Options Summary
- Refreshing Datasets
- Understanding Data Refresh
- Personal Gateway (Power BI Pro and 64-bit Windows)
- Replacing a Dataset and Troubleshooting Refreshing
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- Introduction To Python
- Installation and Working with Python
- Understanding Python variables
- Python basic Operators
- Understanding the Python blocks.
- Python Keyword and Identiers
- Python Comments, Multiline Comments.
- Python Indentation
- Understating the concepts of Operators
- Introduction To Variables
- Variables, expression condition and function
- Global and Local Variables in Python
- Packing and Unpacking Arguments
- Type Casting in Python
- Byte objects vs. string in Python
- Variable Scope
- Python Data Type
- Declaring and using Numeric data types
- Using string data type and string operations
- Understanding Non-numeric data types
- Understanding the concept of Casting and Boolean.
- Strings
- List
- Tuples
- Dictionary
- Sets
- Control Structure & Flow
- Statements if, else, elif
- How to use nested IF and Else in Python
- Loops
- Loops and Control Statements.
- Jumping Statements Break, Continue, pass
- Looping techniques in Python
- How to use Range function in Loop
- Programs for printing Patterns in Python
- How to use if and else with Loop
- Use of Switch Function in Loop
- Elegant way of Python Iteration
- Generator in Python
- How to use nested Loop in Python
- Use If and Else in for and While Loop
- Examples of Looping with Break and Continue Statement
- How to use IN or NOT IN keyword in Python Loop.
- Python Function, Modules and Packages
- Python Syntax
- Function Call
- Return Statement
- Arguments in a function Required, Default, Positional, Variable-length
- Write an Empty Function in Python pass statement.
- Lamda/ Anonymous Function
- *args and **kwargs
- Help function in Python
- Scope and Life Time of Variable in Python Function
- Nested Loop in Python Function
- Recursive Function and Its Advantage and Disadvantage
- Organizing python codes using functions
- Organizing python projects into modules
- Importing own module as well as external modules
- Understanding Packages
- Random functions in python
- Programming using functions, modules & external packages
- Map, Filter and Reduce function with Lambda Function
- More example of Python Function
- List
- What is List.
- List Creation
- List Length
- List Append
- List Insert
- List Remove
- List Append & Extend using + and Keyword
- List Delete
- List related Keyword in Python
- List Revers
- List Sorting
- List having Multiple Reference
- String Split to create a List
- List Indexing
- List Slicing
- List count and Looping
- List Comprehension and Nested Comprehension
- Tuple
- What is Tuple
- Tuple Creation
- Accessing Elements in Tuple
- Changing a Tuple
- Tuple Deletion
- Tuple Count
- Tuple Index
- Tuple Membership
- TupleBuilt in Function (Length, Sort)
- Dictionary
- Dict Creation
- Dict Access (Accessing Dict Values)
- Dict Get Method
- Dict Add or Modify Elements
- Dict Copy
- Dict From Keys.
- Dict Items
- Dict Keys (Updating, Removing and Iterating)
- Dict Values
- Dict Comprehension
- Default Dictionaries
- Ordered Dictionaries
- Looping Dictionaries
- Dict useful methods (Pop, Pop Item, Str , Update etc.)
- Sets
- What is Set
- Set Creation
- Add element to a Set
- Remove elements from a Set
- PythonSet Operations
- Frozen Sets
- Strings
- What is Set
- Set Creation
- Add element to a Set
- Remove elements from a Set
- PythonSet Operations
- Python Exception Handling
- Python Errors and Built-in-Exceptions
- Exception handing Try, Except and Finally
- Catching Exceptions in Python
- Catching Specic Exception in Python
- Raising Exception
- Try and Finally
- Python File Handling
- Opening a File
- Python File Modes
- Closing File
- Writing to a File
- Reading from a File
- Renaming and Deleting Files in Python
- Python Directory and File Management
- List Directories and Files
- Making New Directory
- Changing Directory
- Python Database Interaction
- SQL Database connection using
- Creating and searching tables
- Reading and Storing cong information on database
- Programming using database connections
- Reading an excel
- Working With Excel
- Reading an excel le using Python
- Writing to an excel sheet using Python
- Python| Reading an excel le
- Python | Writing an excel le
- Adjusting Rows and Column using Python
- ArithmeticOperation in Excel le.
- Play with Workbook, Sheets and Cells in Excel using Python
- Creating and Removing Sheets
- Formatting the Excel File Data
- More example of Python Function
- Complete Understanding of OS Module of Python
- Check Dirs. (exist or not)
- How to split path and extension
- How to get user prole detail
- Get the path of Desktop, Documents, Downloads etc.
- Handle the File System Organization using OS
- How to get any les and folders details using OS
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- Data Analysis and Visualization using Pandas.
- Statistics
- Pandas
- Data Analysis and Visualization using NumPy and MatPlotLib
- NumPy
- MatPlotLib
- Introduction to Data Visualization with Seaborn
- Introduction to Seaborn
- Visualizing Two Quantitative Variables
- Visualizing a Categorical and a Quantitative Variable
- Customizing Seaborn Plots
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- Capstone Project
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