Data Analytics Training And Internship Kozhikode Kerala

In today’s digital world, one of the most in-demand professions is Data Analytics. The way data Analytics influence the growth of a company is beyond compare. The invaluable information and data received through data analytics can influence the strategic decision-making of companies regardless of the industry.

Let’s have a look at what data analytics offers:

  • Data Analytics assists a company in identifying hidden patterns.
  • Data Analytics assists a company in correlations.
  • Data Analytics combine methods from computer science and find the latest and new trends from large datasets.
  • Assists in machine learning and statistics.

But is data analytics easy? Let us at Futura Labs offer you some insights and guidance for you to become a data analyst.

How to Become a Data Analyst

To become a professional Data Analyst you have to complete a course on data analytics.

We can assist you with your training.

We are Futura Labs, one of the best Data Analytics Training centres in Kerala.

At Futura Labs, we have designed a thorough training system that can surely help you to become a successful Data Analyst. We have the best industry-experienced professionals and state-of-the-art tools to make your dream of becoming a successful Data Analyst a reality.

Let’s have a look at what we at Future Labs offer you when you enrol in our extensive data analytics course:

  • Industry Relevant Curriculum – At Futura Labs, our professional tutors have years of industry experience. Our tutors are well-versed in the latest trends, methods, tools and technology. Our experts have created this curriculum keeping in mind that our trainees will be ready to meet any challenge the job market may hold for them.
  • Experienced Trainers – At Futura Labs, we have some of the most skilled experts with years of industry experience and a wealth of data analytics insights. Our trainers ensure that every trainee has a full grasp of the concept and has a keen idea of when and where to implement them. We provide them with specific industry-oriented guidance to make them compatible with any industry.
  • Advanced Tools and Technologies – In any industry, knowing the latest tools and technologies is a must. The more familiar you are with the latest data analytics tools and technologies, the more you can implement them in your profession. At Futura Labs, we provide trainees with the latest versions of Python, SQL, R, Tableau and other latest versions of data analytics tools and technologies.
  • Career Support – At Futura Labs, we provide extensive career support. Our support includes resume creation, interview preparation and assistance in job placement. Our aim is to help the trainees transition from education to employment effortless.
  • Flexible Learning Options – Time and distance should not be a hindrance in your training. That’s why we at Futura Labs offer you flexible learning options. To meet different student needs, we offer both offline and online training options. Our flexible training options make sure you don’t have a break in your training, regardless of where you are and how busy you are.
  • Certification – After successful completion of the course, we at Futura Labs present you with a certification that is widely accepted by top business executives. Our certification will improve your reputation and job opportunities.

Why wait when you can transform your life with a data analyst job?

Join hands with Futura Labs and be proficient in data analytics. Enroll now with Futura Labs, gain updated industry insights and sharpen your skills. We help you succeed in the dynamic data analytics profession.

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
     
batchNext Batch
4
December
Calicut(Offline & Online)
16
December
Calicut(Offline & Online)
26
December
Calicut(Offline & Online)
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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    • Data Analytics assists a company in identifying hidden patterns.
    • Data Analytics assists a company in correlations.
    • Data Analytics combine methods from computer science and find the latest and new trends from large datasets.
    • Assists in machine learning and statistics.

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    How to Become a Data Analyst

    To become a professional Data Analyst you have to complete a course on data analytics.

    We can assist you with your training.

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    At Futura Labs, we have designed a thorough training system that can surely help you to become a successful Data Analyst. We have the best industry-experienced professionals and state-of-the-art tools to make your dream of becoming a successful Data Analyst a reality.

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