Data analytics is one of the most in-demand careers in today’s digital age. There is no comparison for the impact data analytics has on a company’s growth. Regardless of the business, the priceless knowledge and data obtained through data analytics can affect how firms make strategic decisions.

Let’s examine the benefits that data analytics can provide:

  • An organization can find hidden patterns with the use of data analytics.
  • Correlations are aided by data analytics for an organization.
  • Data analytics uses a combination of computer science techniques to mine massive datasets for the newest and most innovative trends.
  • Helps with statistics and machine learning.

Is data analytics simple, though? Allow Futura Labs to provide you with some advice and insights so you can become a data analyst.

How to Work in Data Analytics

Completing a data analytics course is a prerequisite for becoming a professional data analyst.

With your training, we can help.

We are Futura Labs, one of Kerala’s top providers of data analytics training.

Our comprehensive training program at Futura Labs will undoubtedly assist you in becoming a proficient data analyst. Our cutting-edge technologies and highly skilled industry professionals can help you realize your dream of becoming a successful data analyst.

Why delay when a career as a data analyst might completely change your life?

Collaborate with Futura Labs and become an expert in data analysis. Enroll with Futura Labs right away to hone your skills and get up-to-date industry information. We support your career success in the dynamic field of data analytics.

DATA ANALYTICS 4 MONTH SYLLABUS

  • Introduction to python
  • Python features
  • Environment setup and setting path
  • Python environmental variables
  • Python Identifiers
  • Reserved words
  • Python variables
  • Standard data types
  • Time
  • Sets
  • Frozen set
  • Data type conversion
  • Python basic operators
  • Decision making Statements
  • Loops
  • Loop control Statements
  • Python functions
  • Modules
  • File handling
  • Directory and file management
  • Python OOPS
  • Constructors
  • Inheritance and types
  • Polymorphism
  • Encapsulation
  • Data abstraction
  • Method overloading
  • Method overriding
  • Operator Overloading
  • Python errors & exception handling
  • Introduction to DBMS
  • Relational and Non-Relational DBMS
  • Introduction to MySQL
  • DDL -Data Definition Language
  • DML –Data Manipulation Language
  • DCL –Data Control Language
  • TCL –Transfer Control Language
  • DQL –Data Query Language
  • Aggregation Functions
  • Wild cards
  • Aliases
  • Joins
  • Functions
  • Introduction to power bi
  • Overview: power bI concepts
  • Report view
  • Report page settings
  • Visualizations
  • Filters
  • Buttons and bookmarks
  • Dax function
  • Table view
  • Model view
  • Power query editor
  • Query settings
  • Dashboard
  • Introduction to tableau
  • Connect data
  • Data source
  • Worksheet
  • Formats
  • Visualizations
  • Calculated fields
  • Sets
  • Groups
  • Pages and Filters
  • Marks
  • Dashboard
  • Story making
  • Introduction to excel
  • Sheet and workbook
  • Absolute cell references
  • Built-in functions
  • Data validation
  • Time and date calculations
  • Text to columns
  • Conditional formatting
  • Exploring styles and clearing
  • Lookup functions
  • Index-match function
  • Pivot table
  • Pivot chart
  • Charts
  • Legend
  • Creating dashboard
  • Visualization using power bi
  • Insights using tableau

DATA ANALYTICS 6 MONTH SYLLABUS

  • Introduction to statistical analysis
  • Quantitative and qualitative data
  • Variable
  • Descriptive statistics
  • Inferential statistics
  • Population and sample
  • Probability
  • Probability distribution
  • Range
  • Skewness
  • Kurtosis
  • Hypothesis testing
  • Random variable
  • Diagrams
  • Cleaning dataset
  • Imputation techniques
  • Correlation and regression
  • Introduction to python
  • Python features
  • Environment setup and setting path
  • Python environmental variables
  • Python Identifiers
  • Reserved words
  • Python variables
  • Standard data types
  • Time module
  • Frozen set
  • Data type conversion
  • Operators
  • Decision making Statements
  • Loops
  • Loop control Statements
  • Functions
  • Lambda Function
  • Modules
  • File handling
  • Directory and file management
  • Python oops
  • Constructors
  • Inheritance and types
  • Polymorphism
  • Encapsulation
  • Data abstraction
  • Method overloading
  • Method overriding
  • Operator Overloading
  • Python errors & exception handling
  • Introduction to python libraries
  • Introduction to numpy
  • Numpy arrays
  • Operations on arrays
  • Indexing & slicing
  • Numpy functions
  • Pandas
  • Introduction to pandas
  • Data manipulation
  • Series
  • Data frames
  • Importing and exporting files
  • Basic functions
  • Date range
  • Group by
  • Merging
  • Concatenation
  • Pivot table
  • Contingency table
  • Matplotlib
  • Introduction to Matplotlib
  • Different Types of Charts
  • Bar chart
  • Line Chart
  • Scatter Chart
  • Pie Chart
  • Introduction to excel
  • Sheet and workbook
  • Excel shortcuts
  • Cell settings
  • Absolute and relative references
  • Built-in functions
  • Data manipulation
  • Sparklines
  • Data validation
  • Time and date calculation
  • Text to columns
  • Conditional formatting
  • Exploring styles and clearing
  • Lookup Functions
  • Arithmetic functions
  • Logical functions
  • Index-match function
  • Pivot table
  • Pivot chart
  • Charts
  • Legend
  • Creating dashboard
  • Data summarization
  • Advanced dashboard creation
  • Visual basic
     
  • Introduction to DBMS
  • Relational and non-relational DBMS
  • Introduction to mysql
  • DDL -Data definition language
  • DML -Data manipulation language
  • DCL -Data control language
  • TCL -Transfer control language
  • DQL -Data query language
  • Constraints
  • Aggregation functions
  • Wild cards
  • Aliases
  • Joins
  • Function
  • My SQL wildcards
  • My SQL aliases
  • My SQL joins
  • Practical illustration
  • Introduction to power bi
  • Overview: Power Bl concepts
  • Report View
  • Report Page settings
  • Visualizations
  • Filters
  • Buttons and bookmarks
  • DAX function
  • Table view
  • Measure tools
  • Model view
  • Constraints
  • Power query editor
  • M language
  • Add column
  • Transform
  • Query settings
  • Dashboard
  • Introduction to tableau
  • Tableau interface
  • Tableau essentials
  • Connecting to data sources
  • Page settings
  • Creating visualizations
  • Filter groups
  • Formulas in tableau
  • Worksheet
  • Interactive charts
  • Different types of charts
  • Calculated field
  • Sets
  • Groups
  • Parameter
  • Advanced visualization
  • Dashboard design and layout
  • Data analysis
  • Storytelling
  • Research about data
  • Excel ai
  • Power Bi with ai
  • Chat with dataset
  • Pandas with Ai
  • Visualization using power bi
  • Insights using tableau
  • Dashboard using Excel
DurationDuration
4 Months, 3 Days a Week, 3 Hours/day
FeeCourse Fees
DurationDuration
6 Months, 3 Days a Week, 3 Hours/day
FeeCourse Fees

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