Data Science Course in Chennai
Login360 training institute is the perfect choice for you if you’re looking for first-rate Data Science training in Chennai. We teach everything from beginning to up-to-date in that subject. The trainers are working as professionals in the IT field for more than ten years. They will teach the students everything they need to know to succeed in the data science field. The Data Science certification course will help you to get placed in top MNC companies.
Best Data Science Course in Chennai
Login360 aims to make you an expert in all the concepts of Data Science, including Data Analytics, Machine Learning Algorithms, Data Modeling, Business Analytics, k-means clustering, and R programming.
Industrial experts design our data science course syllabus with their recent experience in the field. They will guide you on how to adapt to the work atmosphere. Trainers for a data science course are well-experienced, knowledgeable, and have 10+ years of experience in the respective domain.
We offer data science courses for affordable prices with the best coaching, and this session will begin from scratch to the advanced level. It will help you to understand the basics to advanced techniques without struggle.
Data Science Training Institute in Chennai
Login360 is the best data science training institute in Chennai, with a unique specialization. A data science course is ideal for persons interested in statistics which might find this course easy.
Especially a data science course helps improve a person’s analytical skills. Our trainers are real-time working professionals with more than 10 years in top MNC companies.
We provide a ranging infrastructure for data science training in Chennai. Here, we offer lab facilities for all our students. Trainers will give assignments and tasks based on regular classes. Our data science certification course makes you master all the fundamentals of data science.
Data Science Course in Chennai With Placement
We offer a job-oriented data science course in Chennai with placement support. Enhance your career by learning a data science course at Login360 with 100% job assistance.
Data Science is the best course for those who want to Shift their career, and this course includes learning statistics, data analysis, Artificial Intelligence, and Machine Learning. You will be working on real-time projects to enhance your skills.
Login360 will conduct mock interviews to determine your area of interest and help you shine in that field. We will arrange interviews for you based on your interest.
Data Science Course Duration and Fees in Chennai
The Data Science course usually takes the following hours to complete the entire module. And it also depends upon the way you learn the course. Here we list out the Data Science course fee range.
| Level | Course Duration | Fees Structure |
| Basic | 2.5 - 3 Months | 4,000₹ - 6,000₹ |
| Advanced | 2.5 - 3 Months | 8,000₹ - 10,000₹ |
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Why Choose Login360 for Data Science?
Login360 offers the best data science training in Chennai. Our trainers are real-time working IT professionals, and they have excellent knowledge in the data science domain, and they will teach you practicals and make you understand thoroughly.
We will arrange interviews, and before that, we will conduct a mock interview, making the actual interview easy for you. We admit only few members per batch so that trainers can focus on every student.
Login360 provides lab facilities and ranging infrastructure to our students for implementing and executing it will enable you to learn data science skills more practically.
Benefits Of Data Science Course
Data science is majorly about the extracts knowledge from big data sets. Data helps predict the future. In the modern world, data has become the top priority because of the use of data in every business field. In various ways, data has been worthwhile.
Login360 offers 40+ IT training courses in Chennai with trainers with more than 7+ years of experience in the IT industry.
Hands-on training
30+ hours course duration
Industry expert faculties
100% job-oriented training
Updated syllabus
Resume buildup
Mock interviews
Affordable fees structure
Job Opportunities in Data Science
A fast-evolving field, Data Science offers a variety of career options. The demand for data science is increasing at an unheard-of rate due to the creation of apps utilizing Big Data and AI.
You can Work as a
Upcoming In-Demand Jobs
Salary in Data Science
Fresher Data Scientist
₹ 3.4 to 4 LPA
Experienced Data Scientist
₹ 6 to 7.3 LPA
Experts in Data Analyst
₹ 4 to 11.2 LPA
Business Intelligence Developer
₹ 3.6 to 11 LPA
Statistician
₹ 1.5 to 2 LPA
Experienced Data Architect
₹ 13.5 to 23.6 LPA
Data Engineer
₹ 3.3 to 8 LPA
Our Students work in
Data Science Topics Covered
The advanced Data Science course will cover all those aspects of Data Science. The advanced Data Science course topics include:
Course Duration : 3 Months (Weekdays)
- Module 1
- Module 2
- Module 3
- Module 4
- Module 5
- Module 6
- Module 7
- Module 8
- Module 9
- Module 10
- Module 11
- Module 12
- Module 13
- Module 14
- The market trend of Data Science
- Opportunities for Data Science
- What is the need for Data Scientists
- What is Data Science
- Data Science Venn Diagram
- Data Science Use cases
- Real-time Practical
- What is Business Intelligence?
- What is ETL?
- Layers of a Data Warehouse
- OLAP VS OLTP
- Facts and Dimensions
- Big Data tools and it’s uses
- Big Data stack
- Understanding Descriptive vs Predictive vs Prescriptive Analytics
- Difference between Analytics vs. Analysis
- Data Science Project Lifecycle
- Technology Stack Involved in the Lifecycle
- Machine Learning tools
- Development tools
- Using SQL concepts inside Python
- What is Statistics
- Sample Vs Population
- The measure of Central vs Dispersion
- Frequency Distribution
- Cumulative Frequency Distribution
- Mean, Median, Mode
- Quartiles/Percentile
- Anaconda & Python
- Understanding Jupyter Notebooks
- Python Package Installation
- Tableau Installation
- Oracle Database & Server
- Introduction to Tableau
- Data sources
- Concept of List, Data frame, Dictionary
- Connecting to Databases using Python
- Importing data from CSV, text, and Excel
- Converting JSON, XML, to Data frame
- Understanding EDA
- Frequency Distribution
- Analyzing NA, blanks
- Handling missing Values
- Handling Outliers
- Normalization techniques
- Standardization techniques
- Regularization techniques
- Feature Extraction
- Train Test data selection
- Understanding Regression math
- Linear Algebra concepts
- Least Mean Square
- Analyzing Co-relation
- Heat Maps, Pair Plots, Distribution Graphs
- Simple Vs Multiple Linear regression
- Train Test data selection
- Overfitting/ Under fitting/ Optimal Fits
- Handling Categorical Data inside
- Confusion Matrix
- Type I & Type II errors
- Precision Vs Accuracy
- AUC/ROC curve
- TF-IDF and its math Behind
- Understanding the Decision Tree & Bagging
- The math behind Classification and Regression in tree
- Decision Tree concepts
- Using Random Forest for Regression
- K fold Cross Validation
- Model Optimizers
- Hyperparameter Tuning
- Label Encoding
- One hot encoding
- Synonym treatment
- Stemming
- Lemmatization
- Stop words
- Parts Of Speech Tagging
- Understanding the Boosting Concept
- Hyper plane and Kernel
- Learning Rate
- Model Optimizers
- Hyper parameter Tuning
- Real-time Practicals
- Introduction to Pyinstaller
- Understanding Deep learning
- MLP Vs other Deep Learning
- How Neural Network works & Architecture
- Activation functions.
- Model Optimizers
- Hyperparameter Tuning
- Best Practice and when to use DL
- Introduction to Sampling
- Over-sampling and Undersampling
- SMOTE/SMOTENC & Near Miss
- Pros and Cons of sampling
- Introduction to DR
- PCA & its code
- Deployment of Model to Production
Module 1
- The market trend of Data Science
- Opportunities for Data Science
- What is the need for Data Scientists
- What is Data Science
- Data Science Venn Diagram
- Data Science Use cases
Module 2
- What is Business Intelligence?
- What is ETL?
- Layers of a Data Warehouse
- OLAP VS OLTP
- Facts and Dimensions
- Big Data tools and it’s uses
- Big Data stack
Module 3
- Understanding Descriptive vs Predictive vs Prescriptive Analytics
- Difference between Analytics vs. Analysis
- Data Science Project Lifecycle
- Technology Stack Involved in the Lifecycle
- Machine Learning tools
- Development tools
Module 4
- What is Statistics
- Sample Vs Population
- The measure of Central vs Dispersion
- Frequency Distribution
- Cumulative Frequency Distribution
- Mean, Median, Mode
- Quartiles/Percentile
Module 5
- Anaconda & Python
- Understanding Jupyter Notebooks
- Python Package Installation
- Tableau Installation
- Oracle Database & Server
Module 6
- Concept of List, Data frame, Dictionary
- Connecting to Databases using Python
- Importing data from CSV, text, and Excel
- Converting JSON, XML, to Data frame
- Understanding EDA
- Frequency Distribution
- Analyzing NA, blanks
- Using SQL concepts inside Python
Module 7
- Handling missing Values
- Handling Outliers
- Normalization techniques
- Standardization techniques
- Regularization techniques
- Feature Extraction
- Train Test data selection
Module 8
- Understanding Regression math
- Linear Algebra concepts
- Least Mean Square
- Analyzing Co-relation
- Heat Maps, Pair Plots, Distribution Graphs
- Simple Vs Multiple Linear regression
- Train Test data selection
Module 9
- Overfitting/ Under fitting/ Optimal Fits
- Handling Categorical Data inside
- Confusion Matrix
- Type I & Type II errors
- Precision Vs Accuracy
- AUC/ROC curve
Module 10
- Understanding the Decision Tree & Bagging
- The math behind Classification and Regression in tree
- Decision Tree concepts
- Using Random Forest for Regression
- K fold Cross Validation
- Model Optimizers
- Hyperparameter Tuning
Module 11
- Label Encoding
- One hot encoding
- Synonym treatment
- Stemming
- Lemmatization
- Stop words
- Parts Of Speech Tagging
- TF-IDF and its math Behind
Module 12
- Understanding the Boosting Concept
- Hyper plane and Kernel
- Learning Rate
- Model Optimizers
- Hyper parameter Tuning
- Real-time Practicals
Module 13
- Understanding Deep learning
- MLP Vs other Deep Learning
- How Neural Network works & Architecture
- Activation functions.
- Model Optimizers
- Hyperparameter Tuning
- Best Practice and when to use DL
Module 14
- Introduction to Sampling
- Over-sampling and Undersampling
- SMOTE/SMOTENC & Near Miss
- Pros and Cons of sampling
- Introduction to DR
- PCA & its code
- CHAPTER 23: Deployment of Model to Production
- Introduction to Pyinstaller
Module 15
- Introduction to Tableau
- Data sources
- Exploratory Data Analysis
- Clustering Analysis and Inferences using Tableau
- Creating visualizations
- Real-time Practicals
Certification
Login360 provides data science certification after the successful completion of the course. With the data science certification, you can enter the IT industry with an additional qualification.
This certification will add more value to your resume, which will help you to access your desired job positions. It shows that the aspirant has the core knowledge of data science to enter the industry. You are provided with videos, PPTs, assignments, and other practical activities.
You Can get this certification within three months, and this certification course is designed for freshers and working professionals.
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Testimonials
MALAVIKA THANGAVEL
Data Scientist
Harish Venkat
Data Analyst
Mahendran S
Selenium Tester
divya senthilnathan
Digital Marketeer
Login360 is not only the best software training institute in Chennai but also the best software training institute in India. Here all faculties are very good and well experienced in their respective fields. They always worry about how the students will learn and understand the subject easily. Their teaching procedure and subject explanation are great.
Abarna Kumar
Software Tester
Logiya Sunder
Java Developer
Frequently Asked Questions
Is Data Science easy for Beginners?
The student with basic knowledge of math and statistics has an advantage in learning data science. If you are interested in learning data science skills, it’s easy for beginners.
How long does it take to learn a data science course in login360?
The Login360 training institute will take only 30-35 hours to learn the Data Science course. However, duration may depend on your learning ability. If you’re a slow learner, it may take more than the course duration.
Is Data Science a stressful job?
The data science career involves algorithms, scientific methods, and analysis, so it’s pretty stressful to handle. This career is great for the person who enjoys doing these processes.
Why should I learn a data science course in Login360?
Login360 offers the best coaching for data science courses in Chennai.
What various training methods does login360 offer?
Login360 provides many suitable modes of training to the student like: