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

Easy way to IT Job

Datascience Course in Chennai

(3024)
Live Online & Classroom Training
EMI
0% Interest

Boost your career with our Data Science Training in Chennai at SLA Institute. Master advanced data analysis techniques, machine learning, and data-driven strategies to excel in the tech industry.

Our Data Science Certification Course in Chennai offers practical experience through hands-on projects and real-world applications. With expert trainers and strong placement support, you’ll be ready for success in data science roles. Enroll now in our Data Science Offline Course in Chennai and explore the detailed course curriculum to start your journey toward a rewarding career in data science!

 

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+91 89256 88858

Upcoming Batches

Hands On Training
3-5 Real Time Projects
60-100 Practical Assignments
3+ Assessments / Mock Interviews
January 2025
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
January 2025
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 Science Training in Chennai

Our Data Science Offline Course in Chennai aims to provide a solid foundation in Java programming, preparing you for real-world software development. Key objectives include:

  • Master Data Analysis Techniques: Learn how to analyze and interpret complex data to extract meaningful insights and drive business decisions.
  • Understand Machine Learning: Gain hands-on experience with machine learning algorithms, enabling you to build predictive models and enhance data-driven decision-making.
  • Work with Big Data: Learn how to handle and process large datasets using big data tools and techniques to derive actionable insights.
  • Data Visualization Skills: Develop skills in visualizing data using tools like Tableau and Power BI to communicate findings effectively to stakeholders.
  • Real-World Applications: Apply data science techniques to solve real-world business problems through practical projects and case studies.
  • Career-Ready Skills: Acquire the technical expertise needed to excel in data science roles, from data cleaning and analysis to machine learning and AI implementation.

Highly Recommended: Data Full Stack Training in Chennai

Future Scope of Data Science Training in Chennai

Rising Demand for Data Science Professionals

The need for data scientists is expanding rapidly across industries. As businesses focus more on data-driven strategies, skilled data professionals are highly sought after. Enrolling in a Data Science course in Chennai prepares you for this increasing demand, positioning you for success in a growing job market.

Diverse Career Opportunities

Data science offers a broad spectrum of career paths, including roles such as data analysts, data engineers, and machine learning specialists. With the knowledge gained from our Data Science certification course in Chennai, you can explore opportunities in sectors like finance, healthcare, retail, and technology, all of which rely on data science to drive their operations.

Attractive Salary Prospects

Data science professionals enjoy competitive salaries due to the high demand for their skills. Entry-level positions offer promising compensation, and as you gain expertise, especially in niche areas like machine learning or AI, your salary potential increases. Completing our Data Science offline course in Chennai can lead to lucrative career opportunities with attractive pay packages.

Check out: Artificial Intelligence Course in Chennai

Technological Advancements in AI and ML

The future of data science is closely tied to advancements in AI and machine learning. By mastering these technologies through our Data Science training in Chennai, you’ll be equipped to work on cutting-edge projects, driving innovation in fields like automation, predictive analytics, and smart systems. The integration of AI with data science ensures exciting career prospects.

Global Career Opportunities

With data science being a globally recognized field, professionals trained in data science are in demand worldwide. Our Data Science Certification Course in Chennai equips you with skills that can open doors to international job opportunities. Whether you want to work remotely for global clients or explore positions abroad, data science offers worldwide career mobility.

Continuous Learning and Career Growth

The field of data science is constantly evolving, offering continuous learning opportunities. New tools, techniques, and methodologies are regularly introduced, keeping professionals engaged and challenged. By pursuing our Data Science Training in Chennai, you’ll be prepared to adapt to these innovations, ensuring your skills remain relevant and advancing throughout your career.

Achieve Your Goals With SLA

SLA builds your future with comprehensive coursework and unparalleled placement support.
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Datascience Course Syllabus

Download Syllabus

Join SLA Institute for Data Science Offline Course in Chennai and gain expertise in data analysis, machine learning, and statistical modeling. Our Data Science Certification Course in Chennai includes hands-on projects, real-world applications, and strong placement support to ensure your success. This course will equip you with the skills needed to excel in data science roles. Enroll now in our Data Science Training in Chennai and take the first step toward a rewarding career in data science!

Introduction
  • Introduction to Data Analytics
  • Introduction to Business Analytics
  • Understanding Business Applications
  • Data types and data Models
  • Type of Business Analytics
  • Evolution of Analytics
  • Data Science Components
  • Data Scientist Skillset
  • Univariate Data Analysis
  • Introduction to Sampling
Basic Operations in R Programming
  • Introduction to R programming
  • Types of Objects in R
  • Naming standards in R
  • Creating Objects in R
  • Data Structure in R
  • Matrix, Data Frame, String, Vectors
  • Understanding Vectors & Data input in R
  • Lists, Data Elements
  • Creating Data Files using R
Data Handling in R Programming
  • Basic Operations in R – Expressions, Constant Values, Arithmetic, Function Calls, Symbols
  • Sub-setting Data
  • Selecting (Keeping) Variables
  • Excluding (Dropping) Variables
  • Selecting Observations and Selection using Subset Function
  • Merging Data
  • Sorting Data
  • Adding Rows
  • Visualization using R
  • Data Type Conversion
  • Built-In Numeric Functions
  • Built-In Character Functions
  • User Built Functions
  • Control Structures
  • Loop Functions
Introduction to Statistics
  • Basic Statistics
  • Measure of central tendency
  • Types of Distributions
  • Anova
  • F-Test
  • Central Limit Theorem & applications
  • Types of variables
  • Relationships between variables
  • Central Tendency
  • Measures of Central Tendency
  • Kurtosis
  • Skewness
  • Arithmetic Mean / Average
  • Merits & Demerits of Arithmetic Mean
  • Mode, Merits & Demerits of Mode
  • Median, Merits & Demerits of Median
  • Range
  • Concept of Quantiles, Quartiles, percentile
  • Standard Deviation
  • Variance
  • Calculate Variance
  • Covariance
  • Correlation
Introduction to Statistics – 2
  • Hypothesis Testing
  • Multiple Linear Regression
  • Logistic Regression
  • Market Basket Analysis
  • Clustering (Hierarchical Clustering & K-means Clustering)
  • Classification (Decision Trees)
  • Time Series Analysis (Simple Moving Average, Exponential smoothing, ARIMA+)
Introduction to Probability
  • Standard Normal Distribution
  • Normal Distribution
  • Geometric Distribution
  • Poisson Distribution
  • Binomial Distribution
  • Parameters vs. Statistics
  • Probability Mass Function
  • Random Variable
  • Conditional Probability and Independence
  • Unions and Intersections
  • Finding Probability of dataset
  • Probability Terminology
  • Probability Distributions
Data Visualization Techniques
  • Bubble Chart
  • Sparklines
  • Waterfall chart
  • Box Plot
  • Line Charts
  • Frequency Chart
  • Bimodal & Multimodal Histograms
  • Histograms
  • Scatter Plot
  • Pie Chart
  • Bar Graph
  • Line Graph
Introduction to Machine Learning
  • Overview & Terminologies
  • What is Machine Learning?
  • Why Learn?
  • When is Learning required?
  • Data Mining
  • Application Areas and Roles
  • Types of Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement learning
Machine Learning Concepts & Terminologies

Steps in developing a Machine Learning application

  • Key tasks of Machine Learning
  • Modelling Terminologies
  • Learning a Class from Examples
  • Probability and Inference
  • PAC (Probably Approximately Correct) Learning
  • Noise
  • Noise and Model Complexity
  • Triple Trade-Off
  • Association Rules
  • Association Measures
Regression Techniques
  • Concept of Regression
  • Best Fitting line
  • Simple Linear Regression
  • Building regression models using excel
  • Coefficient of determination (R- Squared)
  • Multiple Linear Regression
  • Assumptions of Linear Regression
  • Variable transformation
  • Reading coefficients in MLR
  • Multicollinearity
  • VIF
  • Methods of building Linear regression model in R
  • Model validation techniques
  • Cooks Distance
  • Q-Q Plot
  • Durbin- Watson Test
  • Kolmogorov-Smirnof Test
  • Homoskedasticity of error terms
  • Logistic Regression
  • Applications of logistic regression
  • Concept of odds
  • Concept of Odds Ratio
  • Derivation of logistic regression equation
  • Interpretation of logistic regression output
  • Model building for logistic regression
  • Model validations
  • Confusion Matrix
  • Concept of ROC/AOC Curve
  • KS Test
Market Basket Analysis
  • Applications of Market Basket Analysis
  • What is association Rules
  • Overview of Apriori algorithm
  • Key terminologies in MBA
  • Support
  • Confidence
  • Lift
  • Model building for MBA
  • Transforming sales data to suit MBA
  • MBA Rule selection
  • Ensemble modelling applications using MBA
Time Series Analysis (Forecasting)
  • Model building using ARIMA, ARIMAX, SARIMAX
  • Data De-trending & data differencing
  • KPSS Test
  • Dickey Fuller Test
  • Concept of stationarity
  • Model building using exponential smoothing
  • Model building using simple moving average
  • Time series analysis techniques
  • Components of time series
  • Prerequisites for time series analysis
  • Concept of Time series data
  • Applications of Forecasting
Decision Trees using R
  • Understanding the Concept
  • Internal decision nodes
  • Terminal leaves.
  • Tree induction: Construction of the tree
  • Classification Trees
  • Entropy
  • Selecting Attribute
  • Information Gain
  • Partially learned tree
  • Overfitting
  • Causes for over fitting
  • Overfitting Prevention (Pruning) Methods
  • Reduced Error Pruning
  • Decision trees – Advantages & Drawbacks
  • Ensemble Models
K Means Clustering
  • Parametric Methods Recap
  • Clustering
  • Direct Clustering Method
  • Mixture densities
  • Classes v/s Clusters
  • Hierarchical Clustering
  • Dendogram interpretation
  • Non-Hierarchical Clustering
  • K-Means
  • Distance Metrics
  • K-Means Algorithm
  • K-Means Objective
  • Color Quantization
  • Vector Quantization
Tableau Analytics
  • Tableau Introduction
  • Data connection to Tableau
  • Calculated fields, hierarchy, parameters, sets, groups in Tableau
  • Various visualizations Techniques in Tableau
  • Map based visualization using Tableau
  • Reference Lines
  • Adding Totals, sub totals, Captions
  • Advanced Formatting Options
  • Using Combined Field
  • Show Filter & Use various filter options
  • Data Sorting
  • Create Combined Field
  • Table Calculations
  • Creating Tableau Dashboard
  • Action Filters
  • Creating Story using Tableau
Analytics using Tableau
  • Clustering using Tableau
  • Time series analysis using Tableau
  • Simple Linear Regression using Tableau

Project Practices on Datascience Training

Project 1Stock Market Price Prediction

Build a machine learning model to predict stock prices based on historical data, market trends, and other relevant factors.

Project 2Fraud Detection System

Create a system that identifies fraudulent transactions in financial data by using classification algorithms and anomaly detection techniques.

Project 3Image Classification with Deep Learning

Develop a deep learning model to classify images into different categories, such as identifying objects or facial recognition.

Project 4Churn Prediction Model

Analyze customer data to predict which customers are likely to leave a service, helping businesses take proactive retention measures.

Prerequisites for learning Data Science Training in Chennai

While not mandatory, having some basic knowledge can help you better understand the concepts in Data Science Training in Chennai. Here are a few helpful skills:

  • Basic Programming Skills: Familiarity with programming languages like Python or R can aid in data analysis and manipulation.
  • Math and Statistics: A basic understanding of math, algebra, and statistics is useful for working with data models and analysis.
  • Problem-Solving Ability: Critical thinking and problem-solving skills can help in handling complex data tasks.
  • Knowledge of Databases: Basic knowledge of SQL and working with databases can assist in managing large datasets.
  • Basic Machine Learning Knowledge (Optional): Familiarity with machine learning concepts can be helpful for advanced topics.
  • Curiosity and Eagerness to Learn: Data science is constantly evolving, so a willingness to learn new things is important.

If you lack any of these skills, don’t worry! Our Data Science Training in Chennai with placement at SLA Institute provides beginner-friendly training to help you build these competencies.

Our Data Science Training in Chennai is ideal to:

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

Job Profile in Data Science Training in Chennai

Upon completing Data Science Training in Chennai with Placement, students will qualify for various job roles in the IT industry. Some of these positions are discussed below:

Data Scientist

  • Responsibilities: Analyze complex datasets, build predictive models, and extract actionable insights to help businesses make data-driven decisions.
  • Salary: ₹6,00,000 – ₹12,00,000 per year

Data Analyst

  • Responsibilities: Collect, clean, and analyze data to identify trends, generate reports, and support decision-making processes.
  • Salary: ₹4,00,000 – ₹8,00,000 per year

Machine Learning Engineer

  • Responsibilities: Design, implement, and maintain machine learning models and algorithms to solve business problems and optimize processes.
  • Salary: ₹8,00,000 – ₹15,00,000 per year

Check out: Machine Learning Course in Chennai

Data Engineer

  • Responsibilities: Build and manage data pipelines, ensure data integrity, and prepare data for analysis and modeling.
  • Salary: ₹7,00,000 – ₹14,00,000 per year

Business Intelligence Analyst

  • Responsibilities: Use data analysis tools to help organizations understand market trends, customer behavior, and performance metrics to make informed decisions.
  • Salary: ₹5,00,000 – ₹10,00,000 per year

AI Research Scientist

  • Responsibilities: Conduct research in artificial intelligence, develop new algorithms, and apply them to solve complex problems in various domains.
  • Salary: ₹10,00,000 – ₹20,00,000 per year

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

Datascience Course FAQ

What is Data Science?

Data Science is the field of using algorithms, statistical models, and data analysis techniques to extract insights and solve problems from large datasets for decision-making.

Is Data Science easy or hard?

Data Science can be challenging due to complex concepts, programming skills, and statistical analysis. However, with practice and learning, it becomes easier to master.

What is Data Science used for?

Data Science is used to analyze large datasets, extract meaningful insights, make data-driven decisions, and solve complex problems across various industries like healthcare, finance, and marketing.

Is Data Science enough to get a job?

Yes, Data Science skills are in high demand. With the right training and experience, it can lead to various job opportunities in tech and analytics.

What is the Data Science course fees in Chennai?

The Data Science course fees in Chennai typically range from 25,000 to 50,000, depending on the institute and course offerings, with placement support included.

Does SLA Institute support EMI options?

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

Is Data Science a good career?

Yes, Data Science is a great career with high demand, excellent salary prospects, and opportunities to work in diverse industries like healthcare, finance, and tech.

Does SLA Institute provide Lifetime Placement Support?

Yes, SLA Institute provides Lifetime Placement Support to assist students in securing job placements throughout their careers.

On Average Students Rated The Datascience Course 4.90/5.0
(3024)

I have attended Data Science Course in Chennai at SLA after my engineering graduation as I thought it will be useful to begin my career. The trainers were taking classes patiently and it helped them to understand the concepts easily. They gave me enough time to work out the tasks and guided me throughout the course along with project practices. I thank Janani mam for providing me placement training and it helped to clear the interview rounds of top companies. Overall, good experience at SLA Institute.

RagunathData Architect

Hi, I am Minu. I was working as a software developer in the .Net field. I wanted to upgrade my career in AI and I have joined SLA for Data Science Course in Chennai. It was really a wonderful experience and I have got what is needed for my career enhancement. SLA has excellent trainers and superb placement support to help my career growth. The class and lab atmosphere is very nice and they gave me a lot of time to practice. Thanks a lot, SLA.

Minu GoergeData Analyst

SLA Institute is the best platform to learn Data Science Training in Chennai. The course content is well-structured by industry experts and it is meticulously framed with balanced theory and practical concepts. The trainers at SLA are skilled in every area related to data science profiles and they provide complete hands-on exposure throughout the course. I recommend SLA Institute for beginners and working professionals for their career upliftment.

Ravi GowathanML Engineer

I have joined SLA to begin my career in the data science field and I am really admired for their teaching and coaching. They have a very good course curriculum and they explain the concepts superbly. The placement faculty Ms.Janani helped in providing good coaching and interview arrangements. It helps me getting placed in a good company. All thanks to SLA and the team.

Gowri ManvaniData Scientist

My data science training at SLA went well with the satisfying job in a good company. I have learned what is needed for a job. SLA has very good course content for data science and skilled trainers to offer the best coaching with hands-on sessions. I got excellent guidance for placement things through Janani Mam along with many interview arrangements. Overall I am very happy in learning at SLA.

Shankar ReddyBI Developer
See More Reviews

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