Software Training Institute in Chennai with 100% Placements – SLA Institute

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Data Analytics Course in Chennai

(1567)
Live Online & Classroom Training
EMI
0% Interest

Our Data Analytics Training in Chennai will expose students to some of  the important concepts in Data Analytics ranging from Data sources eg. databases, APIs, files etc, exploratory data analysis, statistical analysis, data visualization to tools and technologies like Tableau and Power BI. This thorough curriculum of our course will make students expert in Data Analytics in a short span of time. Our Data Analytics Course with 100% placement support is designed and curated by some of the leading experts and professionals from the IT industry. That is why our Data Analytics Course is based on newly updated trends in the industry.

Our SLA Institute is guaranteed to place you in a high-paying Data Analyst job with help of our experienced placement officers. SLA Institute’s Course Syllabus for Data Analytics covers all topics that are guaranteed to give you a holistic understanding of Data Analytics.

 

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Upcoming Batches

Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
November 2024
Week days
(Mon-Fri)
Online/Offline

2 Hours Real Time Interactive Technical Training 

1 Hour Aptitude 

1 Hour Communication & Soft Skills

(Suitable for Fresh Jobseekers / Non IT to IT transition)

Course Fee
November 2024
Week ends
(Sat-Sun)
Online/Offline

4 Hours Real Time Interactive Technical Training

(Suitable for working IT Professionals)

Course Fee

Save up to 20% in your Course Fee on our Job Seeker Course Series

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Quick Enquiry

Placement

100% Assistance

Learning

Job-Centered Approach

Timings

Convenient Hrs

Mode

Online & Classroom

Certification

Industry-Accredited

This Course Includes

  • FREE Demo Class
  • 0% EMI Loan Facilities
  • FREE Softskill & Placement Training
  • Tie up with more than 500+ MNCs & Medium Level Companies
  • 100% FREE Placement Assistance
  • Course Completion Certificate
  • Training with Real Time Projects
  • Industry-Based Coaching By MNC IT Professionals
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Expected Criteria for Assured Placement

The following criteria help the placement team guide the candidates to get placed immediately after the course completion through SLA Institute.

  • 80% of coursework completion helps us arrange interviews in required companies.
  • 2 or 3 projects to be done for the selected course to ace the technical round effectively.
  • Ensure attending the placement training right from the first day of the selected course.
  • Practice well with resume building, soft skill, aptitude skill, and profile strengthening.
  • Utilize the internship training program at SLA for the complete technical skills.
  • Collect the course completion certificate and update the copy to the placement team.
  • Ensure your performance indicator meets the expectation of top companies.
  • Always be ready with the updated resume that includes project details done at SLA.
  • Enjoy unlimited interview arrangements along with internal mock interviews.
Have Queries? Ask our Experts

+91 89256 88858

SLA's Distinctive Placement Approach

1

Tech Courses

2

Expert Mentors

3

Assignments & Projects

4

Grooming sessions

5

Mock Interviews

6

Placements

Objectives of Data Analytics Course in Chennai

The main objective of the Data Analytics Course in Chennai is to make students grasp all the concepts in Data Analytics easily. Which is why our Data Analytics course will make students grow into experts in the Data Analytics subject. In our Data Analytics Course students will learn:

  • The syllabus begins with fundamental concepts like – Basics of Python, Power BI and SQL.
  • The syllabus then moves to mid-level topics such as Data Extraction and Analysis Etc.
  • The syllabus then finally goes to advanced level topics ranging from Tableau to Excel.

Future Scope of Data Analytics Course in Chennai

The following are the future scope of learning Data Analytics Course in Chennai:

High Demand Across Industries: Data analytics is indispensable across diverse sectors like finance, healthcare, retail, manufacturing, and technology, driving efficiency, enhancing customer experiences, and guiding strategic decisions. This broad applicability ensures a steady demand for proficient data analysts.

Diverse Career Paths: Training in data analytics opens doors to various roles, including:

  • Data Analyst: Extracting insights to support business decisions.
  • Business Analyst: Using data to uncover opportunities and streamline processes.
  • Data Scientist: Applying advanced analytics and machine learning to tackle complex challenges.
  • Data Engineer: Managing data infrastructure for efficient analysis.
  • Business Intelligence (BI) Developer: Designing solutions for data reporting and analysis.
  • Embracing Emerging Technologies: Advancements in artificial intelligence (AI) and machine learning (ML) present opportunities for data analytics professionals to harness these tools for deeper insights and predictive capabilities.

Big Data Expertise: The exponential growth in data volume necessitates skilled professionals capable of handling and deriving value from large datasets using tools like Hadoop, Spark, and cloud platforms.

High-paying job: The job as a Data Analyst is one of the highest-paying jobs in the industry. The Data Analyst Salary in Chennai for freshers and experienced generally ranges ₹4-20 lakhs annually respectively.

Achieve Your Goals With SLA

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Data Analytics Course Syllabus

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SLA Institute’s Data Analytics Course Syllabus comes with 100% placement support so students have no need to worry about their placements after completing the course. In addition to that the Data Analytics Course Syllabus is also curated with the help of leading professionals and experts from the IT industry. So, everything that our students learn in the Data Analytics course is fully updated and new, which increases their chances of getting placed.

CORE PYTHON
  • Python Introduction & history
  • Color coding schemes
  • Salient features & flavors
  • Application types
  • Language components
  • String handling management
    • String operations – indexing, slicing, ranging
    • String methods – concatenation, repetition, formatting
    • Supporting functions
  • Native data types
    • List
    • Tuple
    • Set
    • Dictionary
  • Decision making statements
    • If
    • If…else
    • If…elif…else
  • Looping statements
    • For loop
    • While loop
  • Function types
    • Built-in functions
    • Math functions
    • User defined functions
    • Recursive functions
    • Lambda functions
  • OOPs
    • Classes and objects
    • init constructor
    • Self-keyword
    • Data abstraction
    • Data encapsulation
    • Polymorphism
    • Inheritance
  • Exception handling
    • Error vs exception
    • Types of error
    • User defined exception handling
    • Exception handler components
    • Try block, except block, finally block
POWER BI INTRODUCTION
  • Data Visualization
  • Reporting Business Intelligence (BI)
  • Traditional BI
  • Self-Serviced BI Cloud Based BI
  • On Premise BI
  • Power BI Products
  • Power BI Desktop (Power Query, Power Pivot, Power View)
  • Flow of Work in Power BI Desktop
  • Power BI Report Server
  • Power BI Service, Power BI Mobile
  • Power BI Architecture
  • A Brief History of Power BI
POWER QUERY
  • Data Transformation
  • Benefits of Data Transformation
  • Shape or Transform Data using Power Query
  • Overview of Power Query / Query Editor
  • Query Editor User Interface
  • The Ribbon (Home, Transform, Add Column, View Tabs)
  • The Queries Pane
  • The Data View / Results Pane
  • The Query Settings Pane, Formula
  • Bar Saving the Work
  • Data types
  • Changing the Data type of a Column Filters in Power Query
  • Auto Filter / Basic Filtering Filter a Column using
  • Text Filters Filter a Column using Number Filters
  • Filter a Column using Date Filters Filter Multiple Columns
  • Remove Columns / Remove Other Columns Name
  • Rename a Column Reorder Columns or Sort Columns
  • Add Column / Custom Column Split Columns Merge
  • Columns PIVOT, UNPIVOT Columns Transpose Columns
  • Header Row or Use First Row as Headers Keep Top Rows
  • Keep Bottom Rows Keep Range of Rows Keep Duplicates
  • Keep Errors Remove Top Rows
  • Remove Bottom Rows
  • Remove Alternative Rows
  • Remove Duplicates, Remove Blank Rows
  • Remove Errors Group Rows / Group By
M LANGUAGE
  • IF..ELSE Conditions
  • TransformColumn()
  • RemoveColumns()
  • SplitColumns()
  • ReplaceValue()
  • Table.Distinct() Options and GROUP BY Options
  • Table.Group()
  • Table.Sort() with Type Conversions
  • PIVOT Operation and Table.Pivot ().
  • List Functions Using Parameters with M Language
DATA MODELING
  • Data Modeling Introduction Relationship
  • Need of Relationship Relationship Types
  • Cardinality in General
    • One-to-One
    • One-to-Many
    • Many-to-One
    • Many-to-Many
  • AutoDetect the relationship
  • Create a new relationship
  • Edit existing relationships
  • Make Relationship Active or Inactive
  • Delete a relationship
DAX
  • What is DAX
  • Calculated Column, Measures
  • DAX Table and Column Name Syntax
  • Creating Calculated Columns
  • Creating Measures
  • Calculated Columns Vs Measures
  • DAX Syntax & Operators
  • Types of Operators
    • Arithmetic Operators
    • Comparison Operators
    • Text Concatenation Operator
    • Logical Operators
DAX FUNCTIONS TYPES
  • Date and Time Functions
    • YEAR, MONTH,DAY
    • WEEKDAY, WEEKNUM FORMAT (Text Function)
    • Month Name, Weekday Name
    • IF
    • TRUE, FALSE NOT,
    • OR, IN, AND
  • Text Function
    • LEN, CONCATENATE
    • LEFT, RIGHT, MID UPPER
    • LOWER TRIM, SUBSTITUTE, BLANK
  • Logical Functions
    • IF TRUE, FALSE NOT
    • OR, IN, AND IF ERROR SWITCH
  • Math & Statistical Functions
    • INT ROUND, ROUNDUP
    • ROUNDDOWN
    • DIVIDE EVEN, ODD
    • POWER, SIGN SQRT
    • FACT SUM, SUMX MIN, MINX MAX
    • MAXX COUNT,
    • COUNTX AVERAGE
    • AVERAGEX COUNTROWS
    • COUNTBLANK
REPORT VIEW
  • Report View User Interface
  • Fields Pane
  • Visualizations pane
  • Ribbon, Views, Pages Tab
  • Canvas Visual Interactions Interaction Type (Filter, Highlight, None)
  • Visual Interactions Default Behavior, Changing the Interaction
  • Grouping and Binning Introduction
  • Using grouping, Creating Groups on Text Columns
  • Using binning, Creating Bins on Number Column and Date Columns
  • Sorting Data in Visuals
  • Changing the Sort Column
  • Changing the Sort Order
  • Sort using column that is not used in the Visualization
  • Sort using the Sort by Column button
  • Hierarchy Introduction
  • Default Date Hierarchy
  • Creating Hierarchy
  • Creating Custom Date Hierarchy
  • REPORT VIEW
  • Change Hierarchy Levels
  • Drill-Up and Drill-Down Reports
  • Data Actions, Drill Down, Drill Up, Show Next Level
  • Expand Next Level Drilling filters other visuals option
VISUALIZATIONS
  • Visualizing Data
  • Why Visualizations
  • Visualization types
  • Create and Format Bar and Column Charts
  • Create and Format Stacked Bar Chart
  • Stacked Column Chart
  • Create and Format Clustered Bar Chart
  • Clustered Column Chart
  • Create and Format 100% Stacked Bar Chart 100% Stacked Column Chart
  • Create and Format Pie and Donut Charts
  • Create and Format Scatter Charts
  • Create and Format Table Visual
  • Matrix Visualization
  • Line and Area Charts
  • Create and Format Line Chart, Area Chart
  • Stacked Area Chart Combo Charts
  • VISUALIZATIONS
  • Create and Format Line and Stacked Column Chart
  • Line and Clustered Column Chart
  • Create and Format Ribbon Chart
  • Waterfall Chart, Funnel Chart
POWER BI SERVICE
  • Power BI Service Introduction
  • Power BI Cloud Architecture
  • Creating Power BI Service Account
  • SIGN IN to Power BI Service Account
  • Publishing Reports to the Power BI service
  • Import / Getting the Report to PBI Service
  • My Workspace / App Workspaces Tabs
  • DATASETS, WORKBOOKS, REPORTS & DASHBOARDS
  • Working with Datasets Creating Reports in Cloud using Published
  • Datasets
  • Creating Dashboards Pin Visuals and Pin LIVE
  • Report Pages to Dashboard
  • Advantages of Dashboards Interacting with
  • Dashboards
  • Formatting Dashboard, Sharing Dashboard
ADVANCED PANDAS FUNCTIONS
  • Group by()
  • Pivot tables()
  • Multi-indexing()
  • merge()
  • concatenate()
  • join()
  • data transformation using apply()
  • map()
  • query()
  • Resampling time series functionality
  • excel writer()
  • pipe()
  • creating dataframes
  • reading CSV files with intrinsic index
  • converting CSV files to dataframes
  • converting dataframes to CSV files
  • converting dataframes to excel file
ADVANCED SQL FUNCTIONS
  • Common Table Expressions (CTE)
  • Recursive CTE’s
  • temporary functions
  • pivoting data with sum() and CASE WHEN
  • Except vs Not in
  • self joins, rank vs dense_rank vs row number
  • ranking data
  • calculating delta values,
  • multiple groupings using rollup
  • calculating running totals
  • computing a moving average
  • date time manipulations
  • Formatting strings, stored methods
  • JOINS
  • Sub Queries
  • Manipulation of date and time
  • procedural data storage
  • Connecting SQL to Python or R language, window Functions
PROJECT
  • Project1 – Product Sales Analysis – Power BI Project and review
  • Project2 – Financial Performance Analysis – Power BI Project and review
  • Project3 – Health care sales Analysis –
  • Intermediate Power BI project and review
  • Project4 – Anamoly detection in Credit card transactions – Intermediate Power BI project and review

Project Practices on Data Analytics Training

Project 1Event Detection in Streaming Data

Analyze continuous data streams (e.g., server logs, sensor data) to promptly detect anomalies and critical events.

Project 2Predictive Maintenance for Manufacturing

Utilize sensor data from industrial equipment to forecast maintenance requirements and prevent unexpected downtime.

Project 3Real-time Traffic Analysis and Optimization

Optimize traffic flow by analyzing real-time data from sensors and GPS devices, and implementing adaptive signal control systems.

Project 4Weather Data Analysis for Agricultural Planning

Optimize agricultural operations by analyzing real-time weather data (e.g., temperature, precipitation) and creating predictive models for crop planning and management.

Prerequisites for learning Data Analytics Course in Chennai

SLA Institute does not demand any prerequisites for any course at all. SLA Institute has courses that cover everything from the fundamentals to advanced topics so whether the candidate is a beginner or an expert they will all be accommodated and taught equally in SLA Institute. However having a fundamental understanding of these concepts below will help you understand the Data Analytics better, but it is completely optional:

  • Basic Computer Proficiency: Essential skills include navigating software applications, managing files, and proficiency in tools like Microsoft Excel, crucial for data manipulation and analysis.
  • Mathematics and Statistics Fundamentals: Understanding algebra, statistics, and probability theory is pivotal. Concepts such as mean, median, mode, standard deviation, and basic probability lay the groundwork for statistical analysis in data analytics.
  • Critical Thinking and Problem-Solving: Data analytics necessitates interpreting data to drive informed decisions. Strong critical thinking and problem-solving abilities are indispensable for discerning data patterns and drawing meaningful insights.
  • Programming Knowledge: Familiarity with languages like Python or R can greatly enhance one’s ability to programmatically manipulate and analyze data. Proficiency in SQL for database querying also proves valuable.

Our Data Analytics Course in Chennai is ideal to:

  • Students eager to excel in Data Analytics
  • Professionals considering transitioning to Data Analytics careers
  • IT professionals aspiring to enhance their Data Analytics skills
  • Data Analysts enthusiastic about expanding their expertise
  • Individuals seeking opportunities in Data Analytics

Job Profile in Data Analytics Course in Chennai

Upon Completing the Data Analytics Course, students will be employed in various job roles in the IT industry some of those job profiles are discussed below:

  • Data Analyst: Responsibilities include analyzing data to derive meaningful insights, preparing reports, and offering data-driven recommendations to enhance business processes and decision-making.
  • Business Analyst: Focuses on understanding business requirements, analyzing data to identify trends and opportunities, and translating insights into actionable strategies to support strategic decision-making.
  • Data Scientist: Utilizes advanced analytics and machine learning techniques to analyze complex datasets, build predictive models, and uncover patterns that drive innovation and solve business challenges.
  • Data Engineer: Designs and maintains data infrastructure for efficient data collection, storage, and analysis. Ensures scalability, reliability, and optimization of data pipelines.
  • Machine Learning Engineer: Our Data Analytics Course in Chennai will train students to be a great Machine Learning Engineer who specializes in developing and deploying machine learning models and algorithms to automate decision-making processes and improve business outcomes through data-driven insights.
  • Quantitative Analyst: Our Data Analytics Course in Chennai will train students to be a very productive Quantitative Analyst who applies statistical and mathematical models to financial data for developing trading strategies, risk management models, and conducting quantitative research in finance and investment sectors.
  • Marketing Analyst: Our Data Analytics Course in Chennai will train students to become expert Marketing Analyst who analyzes marketing data including campaigns, customer behavior, and market trends to optimize strategies, enhance return on investment (ROI), and improve customer engagement.
  • Operations Analyst: SLA Institute offers student knowledge to become an expert in Operations Analyst who focuses on optimizing operational efficiency by analyzing data related to production, supply chain management, and resource allocation to drive improvements and cost savings through our Data Analytics course.
  • Healthcare Data Analyst: SLA Institute creates a great workforce of individuals who specialize in diverse job roles and one of them is Healthcare Data Analyst who analyzes healthcare data to assess patient outcomes, clinical trials, and trends, providing insights to enhance patient care, operational efficiency, and healthcare delivery.

Want to learn with a personalized course curriculum?

The Placement Process at SLA Institute

  • To Foster the employability skills among the students
  • Making the students future-ready
  • Career counseling as and when needed
  • Provide equal chances to all students
  • Providing placement help even after completing the course

Data Analytics Course FAQ

How crucial is data preprocessing in Data Analytics?

Data preprocessing plays a vital role in Data Analytics by addressing tasks like cleaning noisy data, handling missing values, scaling or normalizing data, and transforming variables as needed. Proper preprocessing ensures that the data is suitable for analysis and modeling, which leads to more accurate and reliable insights.

What are the various types of data analysis techniques used in Data Analytics?

Data Analytics encompasses several techniques:

  • Descriptive Analytics: Summarizes data to understand its fundamental characteristics.
  • Diagnostic Analytics: Analyzes data to uncover reasons behind specific outcomes.
  • Predictive Analytics: Predictive Analytics employs past data to predict future outcomes.
  • Prescriptive Analytics: Recommends actions based on analysis to achieve desired objectives.
How are machine learning algorithms applied in Data Analytics?

Machine learning algorithms are pivotal in Data Analytics for diverse tasks such as:

  • Classification: Predicting outcomes like customer churn.
  • Regression: Forecasting variables such as sales figures.
  • Clustering: Grouping similar data points.
  • Anomaly Detection: Identifying unusual patterns like fraud attempts.
What statistical techniques and models are typically covered in Data Analytics courses?

Data Analytics courses commonly cover:

  • Descriptive Statistics: Summarizing data to describe its features.
  • Inferential Statistics: Performing hypothesis testing and establishing confidence intervals.
  • Regression Analysis: Predicting relationships between variables.
  • Time Series Analysis: Analyzing data points over time.
  • Machine Learning Algorithms: Including decision trees, random forests, and clustering techniques.
Does SLA Institute have HR personnel?

Yes, SLA Institute has an HR personnel who will look into students issues and grievances.

Does SLA Institute support EMI options?

Yes, SLA Institute supports EMI options with 0% interest.’

Is data analytics a good career?

Data Analytics is highly regarded for its promising career prospects, driven by strong demand across industries, diverse job opportunities, competitive salaries, continuous learning potential, global applicability, and avenues for impactful contributions and career advancement.

Is Data Analytics difficult to learn?

Learning Data Analytics can be easier or harder depending on what you already know and how complex the topics are. Basic ideas and tools are usually understandable, but getting really good at advanced stuff like machine learning or big data can take a lot of time and effort. But SLA Institute and the experienced trainers that it has, will surely make the learning easy for any students. So at the end it all boils down to the  commitment and the willingness of students to invest effort which can make anything happen.

On Average Students Rated The Data Analytics Course 4.90/5.0
(1567)

I did a Data Analytics Course at SLA Institute. Here everyone is very friendly and my trainer trained me in all the important topics. My counselor gives me full support. The placement support is extremely good here. Now I have got placed as an ML programmer in a company with a good salary. Thanks a lot, SLA.

Paranesh

The training and career guidance provided by SLA is just awesome and fruitful for me to obtain a data analyst job. The way of Deep Learning Training in Chennai at SLA can’t compare with any other institute. They have a well-designed data analytics course curriculum with practical hands-on exposure. They help me develop my skills for performing well in my position and I thank SLA for putting me industry-related knowledge. I recommend SLA to you all.

Lavanya

Good Trainer and a great Institute for learning Data Analytics with Python Courses in Chennai. The trainer taught the concepts very clearly, theoretically, and practically. She guides real-time projects and encourages me to learn by working out on my own. She gave a lot of examples to explain the concepts. The placement training went so well. And I am thankful to SLA for providing me with a good platform to learn for my career.

Nelson

SLA is the best place for learning Data Analytics with Python Programming Language as it provides unlimited practice hours along with good teaching from field experts. I admired the teaching and placement guidance provided by the excellent trainers as per the need of the hour. Thanks for the good coaching and I suggest SLA to my fellow graduates for sure.

Megna Saran.SCEO

The SLA faculty is top-notch and knowledgeable. They provide industry-standard data analytics training in Chennai. My trainers were hands-on and gave me lots of exercises to do. Recently, I was hired as an AI Interaction designer. I am capable of doing well on whatever projects are given to me. Many thanks to SLA for assisting me in starting my career in the field I wanted. For experts and newcomers looking for Data Analytics Training Courses in Chennai, I heartily endorse SLA.

Jegan.TCEO
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