TOP 10 BEST DATA SCIENCE COURSES IN CHENNAI
Are you seeking the best data science course in Chennai with placement opportunities? If that’s the case, you’ve landed on the right page.
Chennai, the capital of Tamil Nadu, is a vibrant and bustling city with a rich history and culture. Founded in the 16th century, Chennai was once a major port city for the British East India Company and played an important role in the spice trade. Today, Chennai is a major economic and cultural center for India, and is home to a diverse population of over 4.5 million people.
The city is known for its beautiful beaches, stunning temples, and delicious food. Chennai is also a major educational hub, and is home to several prestigious universities and colleges. With its rich culture and heritage, Chennai is a city that has something to offer everyone.
To boost business growth and help startups thrive in Chennai, using data science is crucial. When companies invest in data-based plans, they can make smarter choices, spot market trends, and improve how they work. Startups can use data science to come up with new ideas, stay ahead in their industries, and attract investment. Partnering with nearby schools can also help companies find and train skilled people, which will keep growing the data science community in Chennai.
| Institute Rank | Name | Training Delivery Type | Offering Course Since | Fees | Placement Assistance |
| 1 | Digiperform- Digital Career Academy | Online | 2013 | Rs.1,22,720 | 100%* |
| 2 | FITA Academy | Online / Offline | 2012 | Rs.15000- Rs.50000 | 100% |
| 3 | Besant Technologies | Online / Offline | 2011 | Rs.15000- Rs.40000 | 100% |
| 4 | ExcelR | Online | 2014 | Rs.84999 – Rs.115999 | 100% |
| 5 | DataMites | Online / Offline | 2016 | Rs.70,623* | 100% |
| 6 | Cognitec | Online/ Offline |
2001 | Rs.45,000 + 18% GST | 100% |
| 7 | SkillSpire Technologies | Offline | 2020 | Rs.15000 – Rs.36000 | NA |
| 8 | Greens Technology | Online/ Offline |
2014 | Rs.35000 – Rs.55000 | 100% |
| 9 | Infycle Technologies | Online/ Offline |
2011 | Rs.40000 | 100% |
| 10 | ESearch Advisors | Online | 2015 | Rs.40,000 + 18% GST | 100% |
Data science encompasses expertise in a specialized field, computer proficiency, and numerical comprehension, enabling the extraction of vital insights from data. Employing computer programs capable of learning from diverse data types such as numbers, text, images, audio, and more, data scientists craft intelligent systems that perform tasks traditionally human-centric. These systems sift through data, aiding businesses significantly.
Its Importance: Data science acts as an invaluable tool, leveraging existing information comprehensively. Its pivotal role lies in empowering companies and institutions to make informed decisions through extensive data analysis. Like a predictive crystal ball, it enhances fields like finance, healthcare, and marketing, enhancing their efficacy. Moreover, it enhances online experiences (as seen in Netflix recommendations), contributes to urban planning for sustainability, aids disaster preparedness, and promotes environmental care. Ultimately, data science emerges as a transformative force impacting diverse sectors, ranging from business operations to global conservation efforts.
1. Digiperform
Digiperform stands as India’s leading training provider exclusively focused on the digital domain. Our curriculum is meticulously crafted and regularly revised by a content panel comprising more than 50 digital marketing industry experts. This process incorporates feedback and recommendations from 450 proficient corporate entities throughout Asia.
Why Choose Digiperform Online Data Science Course?
Selecting Digiperform’s Online Data Science Course offers a distinctive and highly valuable learning experience for those passionate about data. Here’s why Digiperform excels as the preferred choice for Data Science education:
Expert Industry Trainers : Learning from seasoned professionals is pivotal in mastering Data Science. Our trainers, boasting an average of 8+ years’ experience in top organizations, bring real-world insights to the virtual classroom.
100% Placement Support : Education aims for rewarding careers. Hence, our dedicated Placement Cell ensures assistance in landing your dream Data Science job.
60+ Projects : Emphasizing hands-on learning, our course includes over 60 practical projects, ensuring a 90% practical and 10% theoretical approach for real-world Data Science skills.
Cutting-edge Curriculum: Aligned with international standards, our curriculum offers advanced content and diverse resources such as PPTs, documents, exercises, and quizzes for a comprehensive learning experience.
One-to-one Career Mentorship : Dedicated online support and tailored doubt-clearing sessions by experts ensure guidance aligned with your career aspirations.
Flexible Learning Platform: With 24×7 access to lectures and training content via our LMS, learn at your pace and revisit materials when needed.
Simulation & Mock Interviews : To meet industry demands, our course includes simulation and mock interviews, preparing you thoroughly for actual Data Science job interviews.
Interview Preparation : Specialized training equips you with skills and knowledge required for various Data Science roles, ensuring preparedness for diverse interview scenarios.
Choosing Digiperform’s Online Data Science Course guarantees quality, flexibility, and a curriculum designed to meet Hyderabad’s Data Science enthusiasts’ specific needs. Our commitment to imparting practical skills and industry-relevant knowledge makes us the premier choice for Data Science education.
Data Science Online Course: Advantages
Enrolling in an online data science course brings numerous benefits. Firstly, it allows learning from the convenience of home, cutting commuting time and costs. These courses typically offer flexible schedules, enabling study at preferred times. They provide diverse resources like videos and quizzes for enhanced comprehension. Additionally, online connectivity facilitates interaction with peers and experts for inquiries and assistance. Above all, upon course completion, one gains valuable skills paving the way to thrilling job prospects within the data science domain.
Data Science Course Syllabus
Module 1: Introduction to Data Science | Introduction to the Industry & Buzzwords Industrial application of data science Introduction to different Data Science Techniques Important Software & Tools Career paths & growth in data science |
Module 2: Introduction to Excel
| Introduction to Excel- Interface, Sorting & Filtering,
Excel Reporting- Basic & Conditional Formatting
Essential Excel Formulae
Layouts, Printing and Securing Files |
Module 3: Introduction to Stats
| Introduction to Statistics & It’s Applications Different types of Data Population vs Sample Sampling Techniques Intro: Inferential vs. descriptive statistics |
Module 4: Descriptive Stats Using Excel Datasets | Categorical Variables Visualization Using Excel Charts- FDT, Pie Charts, Bar Charts & Pareto Numerical Variables Visualization of Frequency & Absolute Frequency- Using Histogram, Cross Table & Scatter Plot Measure of Spread ( Mean, Mode , Median) Measure of Variance( Skewness, SD, Variance, Range, Coef. Of Variance, Bivariate Analysis, Covariance & Correlation) |
Module 5: Inferential Stats Using Excel Datasets | Introduction to Probability Permutation & Combinations Types of events Normal distribution Standard Normal distribution Normal vs. Standard Normal distribution Confidence Intervals & Z-Score Hypothesis Testing & It’s Types |
Module 6: Database Design & MySQL | Relational Database theory & Introduction to SQL MySQL Installation Database Creation in the MySQL Workbench Querying in MySQL Joins and Set Operations SQL Practice Case Study Window Functions Case Statements, Stored Routines and Cursors Ø Query Optimisation and Best Practices Ø Problem-Solving Using SQL |
Module 7: Data Visualization Using Advanced Excel
| Introduction LOOKUP functions Pivot Tables WHATIF Analysis Dashboard Creation Recording Macros Advanced Visualizations- PIVOT Charts, Sparklines, Waterfall Charts Data Analysis ToolPak – Regression in Excel |
Module 8: Data Visualization Using Tableau | Introduction to Tableau Introduction What is Data Analytics? Why Data Visualisation? What is Tableau? Why Tableau? Tableau vs Excel and PowerBI Exploratory and Explanatory Analysis Getting started with Tableau Visualizing and Analyzing data with Tableau – I Introduction Bar Charts Line Charts and Filters Area Charts Box plots and Pivoting Maps and Hierarchies Pie Charts Treemaps and Grouping Dashboards Visualizing and Analyzing Data with Tableau – II Introduction Joins and Splits Numeric and String functions Logical and Date functions Histograms and parameters Scatter Plots Dual Axis Charts Top N Parameters and Calculated Fields Stacked bar Charts Dashboards – II and Filter Actions Storytelling Summary |
Module 9: Python Programming
| Installing Anaconda & Basics of Python Introduction to programming languages Compiler vs Interpreter Getting Started With Python Introduction to jupyter Notebooks Identifiers, Keywords Print function Comment, Indentation Data Types Functions Understanding what are functions Defining and calling functions Local and global variables Different types of arguments Map,reduce,filter,lambda and recursive functions Data Structures in Python Introduction Lists Tuples Sets Dictionaries Practice Exercise Summary Operator Input and Output Different Arithmetic , logical and Relational operators Input, Output function Eval function Format Function Control Flow If elif else statement For and while loops Break , continue and Pass statement List and dictionary comprehensions Functions Understanding what are functions Defining and calling functions Local and global variables Different types of arguments Map,reduce,filter,lambda and recursive functions File Handling Purpose of file handling Different function in file handling (open,read, write,close) Different modes (r,w,a,r+,w+,a+) With block Exception Handling, OOPX & Regex What is exception handling Try, except, else and finally block Different types of Exception Concept of Oops Different functions in Regex Metacharacters in Regex |
Module 10: Python For Data Science | NumPy Introduction to NumPy Basics of NumPy Operations Over 1-D Arrays Practice Exercise I Multidimensional Arrays Creating NumPy Arrays Mathematical Operations on NumPy Mathematical Operations on NumPy II Computation Times in NumPy vs Python Lists Practice Exercise II Pandas Introduction to Pandas Basics of Pandas Pandas – Rows and Columns Describing Data Indexing and Slicing Operations on Dataframes Groupby and Aggregate Functions Merging DataFrames Pivot Tables Practice Exercise |
Module 11: Data Visualization Using Python- Matplotlib & Seaborn
| Introduction to Data Visualisation with Matplotlib Introduction to Matplotlib The Necessity of Data Visualisation Visualisations – Some Examples Facts and Dimensions Bar Graph Scatter Plot Line Graph and Histogram Subplots Choosing Plot Types Summary Data Visualisation: Case Study Introduction Case Study: Mind Map Case Study Overview Data Handling and Cleaning: I Data Handling and Cleaning: II Sanity Checks Outliers Analysis with Boxplots Histograms Summary Practice Questions Data Visualization with Seaborn Introduction Distribution Plots Styling Options Pie – Chart and Bar Chart Scatter Plots Pair Plots Revisiting Bar Graphs and Box Plots Heatmaps Line Charts Stacked Bar Charts Case Study Summary Plotly Practice Questions |
Module 12: Exploratory Data Analysis | Data Sourcing Module Introduction Introduction to EDA Public and Private Data Private Data Public Data Web Scraping-I Web Scraping-II Summary Data Cleaning Introduction Data Types Fixing the Rows and Columns Impute/Remove Missing Values Handling Outliers Standardising Values Fixing Invalid Values and Filter Data Practice Questions Summary Univariate Analysis Introduction to Univariate Analysis Categorical Unordered Univariate Analysis Categorical Ordered Univariate Analysis Statistics on Numerical Features Graded Questions Summary Bivariate and Multivariate Analysis Introduction Numeric – Numeric Analysis Correlation vs Causation Numerical – Categorical Analysis Categorical – Categorical Analysis Multivariate Analysis Graded Questions Summary Module Summary |
Module 13: Supervised Learning Model - Regression | Introduction to Simple Linear Regression Introduction to Simple Linear Regression Introduction to machine learning Regression line Best fit line Strength of simple linear regression Simple linear regression in python Assumptions of simple linear regression Reading and understanding the data Hypothesis testing in linear regression Building a linear model Residue analysis and predictions Linear Regression using SKLearn Multiple Linear Regression Motivation-when one variable is not enough Moving from SLR to MLR-new considerations Multi collinearity Dealing with categorical variables Model assessment in comparison Feature selection Multiple Linear Regression in Python Reading and understanding the data Data preparation Initial steps Building the model I & II Residue analysis and predictions Variable selection using RFE Industry Relevance of Linear Regression Linear regression revision Prediction versus projection Media company case study Exploratory data analysis Model building - I, II & III Assessing the model Interpreting the results |
Module 14: Supervised Learning Model - Classification | Univariate Logistic Regression Binary classification Sigmoid curve Finding the best fit sigmoid curve - I Finding the best fit sigmoid curve - II Odds and log Odds Multivariate Logistic Regression - Model Building Multivariate Logistic Regression - Model Building Data cleaning and preparation - I & II Building your first model Feature elimination using RFE Confusion metrics and accuracy Manual feature elimination Multivariate Logistic Regression - Model Evaluation Multivariate Logistic Regression - Model Evaluation Metrics beyond accuracy-sensitivity and specificity Sensitivity and specificity in Python Understanding ROC curve ROC curve in python Finding the optimal threshold Model evaluation metrics - exercise Precision and recall Making predictions Logistic Regression - Industry Applications - Part I Getting familiar with logistic regression Nuances of logistic regression-sample selection Nuances of logistic regression-segmentation Nuances of logistic impression-variable transformation-I, II & III Logistic Regression: Industry Applications - Part II Model evaluation - A second look Model validation and importance of stability Tracking of model performance over time Logistic Regression - Industry Applications - Part II Commonly face challenges in implementation of logistic regression Model evaluation - A second look Model validation and importance of stability Tracking of model performance over time |
Module 15: Advanced Machine Learning | Unsupervised Learning: Clustering Introduction to Clustering K Means Clustering Executing K Means in Python Hierarchical Clustering Business Problem Solving Introduction to Business Problem Solving Case Study Demonstrationchurn example Practice Questions Tree Models Introduction to Decision Trees Algorithms for Decision Tree Construction Hyperparameter Tuning in Decision Trees Ensembles and Random Forests Time Series Forecasting - I (BA) Introduction to Time Series Smoothing Techniques Time Series Forecasting - II (BA) Introduction to AR Models Building AR Models Model Selection Principles of Model Selection Model Building and Evaluation |
Module 16: AI- NLP, Neural Networks & Deep Learning | Introduction to NLP What is NLP? History and evolution of NLP Applications of NLP Challenges in NLP Overview of NLP pipeline Corpus and Corpus Linguistics NLTK Toolkit Introduction to the NLTK toolkit Preprocessing text data with NLTK Basic NLP tasks using NLTK (e.g., Part-ofSpeech Tagging, Named Entity Recognition) Stemming and Lemmatization WordNet in NLTK Chunking and Chinking Sentiment Analysis with NLTK Tokenization and Topic Modeling Tokenization in NLP Bag-of-Words representation Topic Modeling with LDA Latent Semantic Analysis Word Embeddings Sentiment Analysis Project: Introduction to Sentiment Analysis Sentiment Analysis using supervised and unsupervised methods Building a Sentiment Analysis model with Python Evaluating Sentiment Analysis models AI vs Deep Learning vs ML Introduction to Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) Applications of AI, ML, and DL Differences between AI, ML and DL The Concept of Neural Networks Introduction to Neural Networks Types of Neural Networks Layers in Neural Networks Activation Functions Neural Networks - Feed-forward, Convolutional, Recurrent Feed-forward Neural Networks Convolutional Neural Networks Recurrent Neural Networks Applications of Neural Networks Deep Learning Project Building a Deep Learning model with Python Image Classification with Convolutional Neural Networks Natural Language Processing with Recurrent Neural Networks Natural Language Processing with Recurrent Neural Networks |
Data Science Projects
Major Projects
Customer Lifetime Value Calculation:
Utilizing SQL, determine the revenue generated by customers over their association with the business, estimating their lifetime value.
Forecasting Customer Churn:
Create a predictive model in SQL to identify potential churners by analyzing transaction history and behavior.
E-Commerce Sales Dashboard:
Develop an interactive Tableau and SQL-powered dashboard to analyze retail sales data, extract trends, and facilitate data-driven decisions.
Customer Segmentation Analysis:
Construct a Tableau-based dashboard to segment customers by demographics, behavior, and purchasing patterns.
Movie Recommendation System:
Build a movie recommendation system in Python using Pandas, NumPy, and Scikit-Learn to suggest films based on user preferences and ratings.
Twitter Sentiment Analysis:
Utilize Python, NLTK, and TextBlob for sentiment analysis on Twitter data, assessing sentiment around specific topics.
Visualizing COVID-19 Insights:
Use Python with Matplotlib, Seaborn, and Plotly to visualize COVID-19 impact across regions and countries.
Stock Market Data Visualization:
Employ Python libraries like Pandas, Matplotlib, and Bokeh to visualize stock market trends and patterns.
Airbnb Data Exploration:
Conduct exploratory analysis on Airbnb data to reveal insights into listings across cities.
Bike Sharing Usage Analysis:
Perform exploratory data analysis on bike sharing data to identify usage patterns and influencing factors.
House Price Prediction:
Develop a regression model using Python and Scikit-Learn to forecast house prices based on location and property characteristics.
Credit Risk Assessment:
Build a classification model in Python using Scikit-Learn to assess credit risk for loan applicants.
Sales Forecasting using Time Series Analysis:
Construct time series forecasting models like ARIMA and LSTM to predict future sales trends.
Product Review Sentiment Analysis:
Utilize NLP techniques such as Word Embeddings and RNN to analyze product reviews and customer sentiments.
Deep Learning Image Segmentation:
Implement advanced deep learning techniques like FCN and U-Net to segment objects in images.
Transformer-Based Language Translation:
Develop machine translation models using advanced deep learning methods like Transformers for text translation between languages.
Case Studies & Assignments:
- Healthcare Feedback Analysis
- Management Dashboard Development
- Retail Sales Report Analysis
- Software Employee Data Analysis
- Industrial Dataset Comparison
- Visualizations: Various graphs & charts
- Patient Disease Probability Analysis
- Car Model & Menu Item Analysis
- Manufacturing Product Classification
- Customer Complaint Resolution
- Product Rating & Productivity Analysis
- New Product Requirement Analysis
- Inventory Management Systems
- Sales Trend & Staffing Planning
- Pricing Strategy & Financial Modeling
- Sales & Operations Dashboard
- Reporting Automation in Healthcare & Construction
- Retail Sales Opportunity Analysis
- Accounting Firm Statement Assessment
- FMCG Marketing Spend Impact Analysis
- Transportation Pricing Model Analysis
Data Science Placements
We offer dedicated support for placements ensuring 100% assistance. Our specialized placement cell is committed to aiding you in securing your desired job opportunity.
Data science course fees
Master Program in Data Science Fees: 1,22,720
Contact Information
Digiperform Corporate Office: C-30, Third Floor, Sector-2, Near Sec-15 Metro Station, Noida, Uttar Pradesh 201301, India
Email: contact@digiperform.com
Phone: +91-8527-611-500
Website: www.digiperform.com
FITA (Focus’d IT Academy) is a training and job placement company managed by IT professionals with more than a decade of experience in leading multinational firms. They have a presence in Chennai, Bangalore, Madurai, and Coimbatore.
Their training approach emphasizes practical learning, enabling students to immerse themselves in real-life situations involving advanced technologies. The instructors are sourced from multinational corporations, offering students authentic insights into corporate settings.
Course Curriculum
- Introduction to Data Science
- Data Science with Python: Introduction to Python
- List, Ranges & Tuples in Python
- Python Dictionaries and Sets
- Input and Output in Python
- Python functions
- Python Exceptions Handling
- Python Regular Expressions
- Data Manipulation using Python
- Understanding Machine Learning Models
- Understanding Machine Learning Algorithms
- Exploring Supervised Learning Algorithms
- Exploring Un-Supervised Learning Algorithms
- Understanding Hypothesis Testing
- Overview Reinforcement Learning Algorithm
- Data Science with R: Introduction to R Programming
- R Programming Basics
- Functions in R
- Working with External Data
- Data Visualization with R
- Exploring Statistical Computations using R
- Packages in R
- Understanding Machine Learning Models
- Understanding Machine Learning Algorithms
- Exploring Supervised Learning Algorithms
- Exploring Un-Supervised Learning Algorithms
- Understanding Hypothesis Testing
- Overview Reinforcement Learning Algorithm
Course Highlights
- FITA Academy offers a comprehensive Data Science Course that combines theoretical concepts with practical applications.
- Elaborate courseware covering various aspects such as Python/R with Data Science.
- Students can build models using Data Science algorithms, analyze datasets from real-world environments, and create interactive visualizations to practice what they learn.
- The Data Science Training in Chennai has flexible batch timings that allow us to provide classes to students on weekends, weekdays, and also provide fast-track sessions.
- FITA Academy has over 1,500+ partners with high demand for Data Scientists, Data Analysts and many other roles related to the field, with whom we are collaborating to provide placement support.
- FITA Academy provides 100% Placement Assistance to all students who successfully complete the training.
| Name | FITA Academy |
| Course Duration | 180 Hours |
| Website | https://www.fita.in/ |
| Address: | No 14, Block No, 338, 2nd Ave, Anna Nagar, Chennai 600 040, Tamil Nadu Landmark: Next to Santhosh Super Market |
| Fees: | Rs.15000- Rs.50000 |
| Avg. Google Rating: | 4.8 |
| Offering DM Training in Chennai Since: | 2012 |
| Branches in India: | 5 |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online /Offline |
Besant Technologies, a prominent player in the IT software training industry, occupies a highly esteemed position in a short span of time. Running a company involves social processes like planning, control, coordination, and motivation. Our Besant Technologies branches in Chennai and Bangalore are meticulously organized. They have coordinators who manage subjects, lectures, issues, and wrap-ups effectively.
Course Curriculum
- Data Science with Python
- Machine Learning
- Artificial Intelligence
- Deep Learning
- Tableau
- SQL
Course Highlights
- Convenient learning format
- Dedicated career services
- Learn from the best
- Structured program with dedicated support
- Hands on learning
| Name | Besant Technologies |
| Course Duration | 3-6 Months |
| Website | https://www.besanttechnologies.com/ |
| Address: | No 4/217A, 2nd Floor, Jeeva Tower, OMR, Siruseri, opposite A2B Restaurant, Egattur, Chennai, Tamil Nadu 600130 |
| Fees: | Rs.15000- Rs.40000 |
| Avg. Google Rating: | 4.7 |
| Offering DM Training in Chennai Since: | 2011 |
| Branches in India: | 15+ |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online /Offline |
Established in 2014, ExcelR has evolved into a prominent leader in the Training and Consulting realm, supporting learners and professionals worldwide by delivering high-quality classroom and online training. Our team comprises dedicated experts devoted to meeting industry demands amidst ever-evolving technological advancements.
Headquartered in the USA and with a presence in the UK, Middle East, Australia, Netherlands, and India, we have established a strong global presence, catering to students from diverse locations. Our passionate team has successfully trained over 140,000 individuals in various domains such as Data Science, Project Management, ServiceNow, and Digital Marketing, aiming to elevate your expertise and advance your career prospects!
Course Curriculum
- Module 1 – Data Science Project Lifecycle
- Module 2 – Introduction To Basic Statistics Using R And Python
- Module 3 – Probability And Hypothesis Testing
- Module 4 -Exploratory Data Analysis -1
- Module 5 – Linear Regression
- Module 6 – Logistic Regression
- Module – 7 Deployment
- Module 8 – Data Mining Unsupervised Clustering
- Module 9 – Dimension Reduction Techniques
- Module 10 – Association Rules
- Module 11 – Recommender System
- Module 12 – Introduction To Supervised Machine Learning
- Module 13 – Decision Tree
- Module 14 – Exploratory Data Analysis – 2
- Module 15: Feature Engineering
- Module 16: Model Validation Methods
- Module 17:Ensembled Techniques
- Module 18 – KNN And Support Vector Machines
- Module 19 – Regularization Techniques
- Module 20 – Neural Networks
- Module 21 – Text Mining
- Module 22 – Natural Language Processing
- Module 23 – Naive Bayes
- Module 24 – Forecasting
- Module 25 – Survival Analysis
- Module 26 – End To End Project Description With Deployment
- Assignments/Projects/Placement Support
- Module 27 – Assignments
- Module 28 – Projects
- Module 29 – Resume Prep And Interview Support
- Value added courses
- Module 30 – Basics Of Hadoop And Spark
- Module 31 – Basics Of R
- Module 32 – Basics Of Python
- Module 33 – Basics Of MYSQL
- Module 34 – Tableau
- Module 35 – Artificial Intelligence (AI)
- Module 36 – ChatGPT
Course Highlights:
- Industry-relevant curriculum
- Expert instructors
- Hands-on learning
- Career support
| Name | ExcelR |
| Course Duration | 6 Months |
| Website | https://www.excelr.com/ |
| Address: | 857, Poonamallee High Rd, Kilpauk, Chennai, Tamil Nadu 600010 |
| Fees: | Rs.84999 – Rs.115999 |
| Avg. Google Rating: | 4.8 |
| Offering DM Training in Chennai Since: | 2014 |
| Branches in India: | 12+ |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online |
DataMites is an institution based in Chennai that specializes in providing education in data science. They offer focused coaching in Data Science, Machine Learning, Deep Learning, Artificial Intelligence, the Internet of Things, and Python Learning. Their goal is to facilitate comprehensive learning in these areas at an affordable price. The real-time training they offer is high-quality and caters to individuals looking to deepen their understanding in these subjects.
At DataMites, their primary objective is to cultivate professionals who can confidently navigate the complexities of the analytical field. Undoubtedly, having a solid grasp of new technologies can lead to numerous unforeseen advantages.
Course Curriculum
- PYTHON FOUNDATION – 6 MODULES
- DATA SCIENCE FOUNDATION – 7 MODULES
- MACHINE LEARNING EXPERT – 12 MODULES
- ADVANCED DATA SCIENCE – 8 MODULES
- VERSION CONTROL WITH GIT – 6 MODULES
- BIG DATA FOUNDATION – 6 MODULES
- CERTIFIED BI ANALYST – 6 MODULES
- DATABASE: SQL AND MONGODB – 7 MODULES
- ARTIFICIAL INTELLIGENCE FOUNDATION – 6 MODULES
| Name | DataMites |
| Course Duration | 3 Months + 4 Months Live Project |
| Website | https://datamites.com/ |
| Address: | IndiQube Brigade Vantage, 2nd Floor, Sy. No. 284/21B, Santhosh Nagar, Karunanidhi Nagar, Perungudi, Chennai, Tamil Nadu 600096 |
| Fees: | Rs.70,623* |
| Avg. Google Rating: | 4.9 |
| Offering DM Training in Chennai Since: | 2016 |
| Branches in India: | 50+ |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online /Offline |
Cognitec serves as a data science training center that offers comprehensive training and placement assistance to newcomers seeking a fresh career start. They provide outstanding training tailored for professionals aiming for progress in the field of Data Science. The team at Cognitec is led by highly proficient industry experts with over a decade of experience in Data Science training.
These skilled professionals act as trainers, delivering top-notch instruction in a premier learning setting, catering to the individual needs of each student to empower them to succeed in their careers.
Course Curriculum
- Python for data-science
- Diploma course in data-analytics
- Data visualization using power-bi
- Data visualization using tableau
- Masters program in data-science and ai
- Data science-course
- Data analytics-course
- Java for Professionals
- Python for Professionals
Course Highlights
- Customized Training Programs
- 100% Live Class
- Business Specific Curriculum
- Unlimited learning
- Tailored Courses
- Business Specific learning
- Job Assistance
- Career Enhancement
| Name | Cognitec |
| Course Duration | 6 Months |
| Website | https://cognitec.in/ |
| Address: | 1St Floor, II Avenue, AC, 3, opp. to Ayyappan Temple, next to Louis Phillippe, Anna Nagar, Chennai, Tamil Nadu 600040 |
| Fees: | Rs.45,000 + 18% GST |
| Avg. Google Rating: | 5 |
| Offering DM Training in Chennai Since: | 2001 |
| Branches in India: | 3 |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online /Offline |
SkillSpire Technologies is a leading data science institute, offering comprehensive training in cutting-edge technologies. With expert instructors and hands-on learning, we empower students with the skills needed in the dynamic field of data science.
Course Curriculum
- Certification in Advanced Data Analytics
- Certification in Advanced Data Science
- SQL for Data Analysis
Course Highlights:
- Learn from Experts
- Live Online/Classroom Training
- Work with Real World Problems
- 1:1 Doubt Clearing Session
- Discounted Course Fee
- Placement Assistance
| Name | SkillSpire Technologies |
| Course Duration | 3-6 Months |
| Website | https://skillspiretechnologies.com/ |
| Address: | 873, 17th Main Rd, Anna Nagar West, Anna Nagar, Chennai, Tamil Nadu 600040 |
| Fees: | Rs.15000 – Rs.36000 |
| Avg. Google Rating: | 4.9 |
| Offering DM Training in Chennai Since: | 2020 |
| Branches in India: | 1 |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Offline |
Greens Technology, located in Vadapalani, Chennai, stands out as a top-tier Training and Placement Institute. Renowned for its practical approach, our courses offer hands-on experience in competitive technologies, facilitated by MNC employees for real-world insights.
With over 150+ software courses in Anna Nagar, our training methodology is geared towards securing corporate job placements. We assure success through practical training and live projects, covering popular courses like Oracle, Selenium, Java, AWS, Salesforce, Python, Hadoop, MSBI, Blockchain, Data Science, Workday, Pega, Web Designing, VMWare, Pentaho, SAS, Teradata, Cognos, Ruby on Rails, and more.
Course Curriculum
- INTRODUCTION TO R
- UNDERSTANDING R DATA STRUCTURE
- IMPORTING DATA
- MANIPULATING DATA
- USING FUNCTIONS IN R
- R PROGRAMMING
- CHARTS AND PLOTS
- MACHINE LEARNING ALGORITHM:
- STATISTICS:
- LEADING TOPICS:
Course Highlights
- Quality Training with Hands on Experience.
- Real Time Project based Training.
- Convenient batch timings for Regular / Fast-track / Weekend
- Career Counseling and Support.
- Unlimited Lab availability.
- Experienced and Certified Trainer from top MNC
- EBooks availability for every Technology.
- Software Installation on laptops.
- Training on Communication Skills, Aptitude, Mock Test to increase Students Employability.
- Live projects in Development, Testing and Administration
- Resume Formation Assistance.
- Interview Tips and Preparation will be covered along with course
- 100% Free Placement Support
- Global Certification center
| Name | Greens Technology |
| Course Duration | 3-6 Months |
| Website | https://greenstech.in/vadapalani%20Website/index.html |
| Address: | 79, 100 Feet Rd, Thiru Nagar Colony, NGO Colony, Vadapalani, Chennai, Tamil Nadu 600026. |
| Fees: | Rs.35000 – Rs.55000 |
| Avg. Google Rating: | 4.8 |
| Offering DM Training in Chennai Since: | 2014 |
| Branches in India: | 12+ |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online /Offline |
Infycle Technologies is a leading software training institute in Chennai, India. They offer a wide range of courses, including software development, data science, and digital marketing. Infycle Technologies is known for its high-quality instruction and its commitment to helping students succeed in their careers. The institute has a strong track record of placing students in top IT companies.
Course Curriculum
- Data Science Introduction
- Enterprise Data Science Intro
- Python
- Advanced Python
- Statistics
- Descriptive Statistics
- Regression
- Data Science Project Stages
- Data Preprocessing
- Regression Advanced
- Data On Environment
Course Highlights
- The institute has state-of-the-art facilities and equipment that help the students to get hands-on experience.
- Incycle also provides study materials, online resources, and 24/7 support to its students.
- The institute offers online and offline courses, making it convenient for the students to choose the mode of learning that suits them best.
| Name | Infycle Technologies |
| Course Duration | 500 Hours |
| Website | https://infycletechnologies.com/ |
| Address: | 1/581A, Jeeva Complex, 200Ft Link Road Thoraipakkam, Old Mahabalipuram Road, Chennai, Tamil Nadu – 600097 Landmark: Near To Chennai One IT SEZ, Thoraipakkam |
| Fees: | Rs.40,000 |
| Avg. Google Rating: | 4.9 |
| Offering DM Training in Chennai Since: | 2011 |
| Branches in India: | 2 |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online/Offline |
ESearch Advisors is an institution at the forefront of digital marketing and data science education. Renowned for its comprehensive programs, it empowers aspiring professionals with cutting-edge skills in digital strategies, analytics, and data-driven decision-making. With a dynamic curriculum and industry-expert faculty, ESearch Advisors is committed to nurturing talent, fostering innovation, and shaping the next generation of adept digital marketers and data scientists.
Course Curriculum
- Module 1: Introduction to Data Science
- Module 2: Python Programming
- Module 3: Data Cleaning and Preprocessing
- Module 4: Exploratory Data Analysis (EDA)
- Module 4: Exploratory Data Analysis (EDA)
- Module 6: Deep Learning
- Module 7: Natural Language Processing (NLP)
- Module 8: Big Data
- Module 9: Data Science Applications
- Module 10: Data Science Ethics
- Module 11: Case Studies
- Module 12: Data Science Projects
Course Highlights
- GET CERTIFIED AS DATA SCIENTIST IN SHORT TIME
- GET TRAINED FROM 100 YEARS OF EXPERTS EXPERIENCE
- SEEK 100% JOB ASSISTANCE
- FEASIBLE LEARNING OPPORTUNITY
| Name | ESearch Advisors |
| Course Duration | 6 Months |
| Website | https://www.esearchadvisors.com/ |
| Address: | Old No: 10, New No : 18 Jayammal Road, Anna Salai, Teynampet, Chennai, Tamil Nadu 600018, India |
| Fees: | Rs.40,000 + 18% GST |
| Avg. Google Rating: | 4.7 |
| Offering DM Training in Chennai Since: | 2015 |
| Branches in India: | 1 |
| Flagship Course Names: | NA |
| Exclusive Data Science Training Institute: | No |
| Training Delivery Model | Online |
Who should learn Data Science in Chennai?
Data Science in Chennai appeals to a broad spectrum of individuals seeking to delve into the world of analytics and technology. It’s an ideal field for aspiring professionals aiming to decode complex data sets, individuals keen on leveraging insights for informed decision-making, and tech enthusiasts fascinated by the fusion of statistics, programming, and domain expertise. From IT professionals, engineers, and business analysts to recent graduates seeking a lucrative career path, Data Science in Chennai opens doors to diverse opportunities in industries spanning finance, healthcare, retail, and more.
Why should you study Data Science?
Having just a graduation degree is insufficient in today’s landscape. With outdated course structures and a vast pool of graduates, students must acquire specific, practical skills to stand out in the competitive field.
The demand for Data Science professionals is soaring, with predictions of India creating over 11 million job openings in the next five years. Experts anticipate a remarkable 200% increase by 2026.
This surge offers a remarkable opportunity for individuals to pursue a lucrative career. Freshers entering the realm of data science can expect salaries averaging between 9 to 12 lakhs per annum. Moreover, these positions demonstrate impressive year-on-year growth potential, ensuring a prosperous professional journey.
Career Scope in Data Science in Chennai
The career scope in Data Science within Chennai is immensely promising. With a burgeoning tech landscape, the demand for skilled professionals in data analysis and interpretation is on the rise. Numerous industries such as IT, finance, healthcare, and more seek adept Data Scientists to extract meaningful insights. Chennai’s thriving job market offers a multitude of opportunities for those passionate about leveraging data for informed decision-making. Aspiring individuals can anticipate lucrative roles with competitive salaries and significant career growth prospects. Embracing a career in Data Science in Chennai presents an exciting pathway into a dynamic and thriving industry, ripe with possibilities for innovation and advancement.
Mastering Data Science Tools
“Embark on a journey into the field of data science with Digiperform’s ‘Mastering Data Science Tools’ program. This course immerses you in Python, R programming, and cutting-edge machine learning techniques to skillfully analyze data and extract meaningful insights. Gain hands-on experience with industry-relevant tools, equipping yourself to tackle real-world data challenges effectively. Elevate your expertise in data science and open up new career prospects through Digiperform’s thorough and practical training.”
Data Science Salaries for Freshers in Chennai
Data science is a rapidly growing field with a high demand for skilled professionals. Freshers in Chennai can expect to earn a competitive salary, with the average annual salary for entry-level data scientists ranging from ₹3.5 Lakhs to ₹6.8 Lakhs per year. This is significantly higher than the average starting salary for all occupations in India, which is around ₹2.5 Lakhs per year.
Factors Affecting Data Science Freshers’ Salaries in Chennai
Several factors can affect the starting salary of a data science fresher in Chennai, including:
Educational Qualifications: A strong academic background in mathematics, statistics, or computer science is highly valued by employers. A master’s degree or Ph.D. can also command a higher salary.
Technical Skills: Employers look for freshers with proficiency in data analysis tools and programming languages such as Python, R, and SQL. Experience with machine learning and artificial intelligence (AI) is also a plus.
Domain Expertise: Knowledge of a particular industry or domain can increase a fresher’s earning potential. For instance, freshers with expertise in healthcare, finance, or e-commerce are often in high demand.
Communication Skills: Effective communication is crucial for data scientists, as they need to explain complex technical concepts to non-technical stakeholders. Strong written and verbal communication skills can make a fresher more attractive to potential employers.
Table of Average Data Science Salaries for Freshers in Chennai
| Experience Level | Average Annual Salary (Lakhs) |
| Less than 1 year | 3.5 – 4.5 |
| 1 – 2 years | 4.5 – 5.5 |
| 2 – 3 years | 5.5 – 6.8 |
Current Job Opening In Data Science in Chennai
Multiple job openings in Data Science are currently available in Chennai. Companies in the city actively seek data scientists to analyze and interpret data effectively. These roles necessitate expertise in data analysis, machine learning, and programming. Individuals possessing the requisite qualifications and skills are encouraged to apply for these vacancies. Data science positions span various sectors such as IT, healthcare, finance, and others, offering a chance to contribute to informed decision-making for businesses. Chennai presents an enticing opportunity for those inclined towards a career in Data Science, with diverse job prospects awaiting. Explore websites like Naukri.com, Linkedin.com, Indeed.com, and more for detailed listings.
FAQs: Data Science Course
What factors should I consider when choosing a data science institute?
When selecting a Data Science institute, consider factors such as curriculum relevance to industry demands, faculty expertise and experience in the field, access to real-world projects or internships, alumni success stories and placements, technological resources and tools provided, flexibility in learning options, support for continuous learning and upskilling, and the institute's reputation within the Data Science community. These aspects ensure a holistic and practical learning experience.
How are the faculty members or instructors selected for teaching Data Science?
At Digiperform, our faculty selection process for teaching Data Science involves meticulous screening of experienced professionals possessing industry expertise and teaching proficiency. We prioritize individuals with extensive practical exposure and a proven track record in Data Science domains. Our selection criteria emphasize a blend of practical skills, teaching abilities, and a commitment to fostering an engaging learning environment, ensuring our students receive top-notch instruction for mastering Data Science concepts.
How can I get started with a data science career?
To embark on a Data Science career journey, begin by grasping fundamental concepts through online courses or workshops. Gain proficiency in programming languages like Python or R, familiarize with statistical analysis, and explore machine learning algorithms. Practical application via projects or internships is crucial. Seek mentorship and stay updated with industry trends to develop a strong foundation for a successful Data Science career. Digiperform offers comprehensive courses aiding in this professional transition.
What is the placement rate for data science courses?
At Digiperform, our Data Science courses boast a robust placement record. With a dedication to grooming skilled professionals, we've achieved an impressive placement rate averaging around 100%. Our curriculum emphasizes practical learning, industry-relevant projects, and mentorship, ensuring graduates are job-ready. Collaborations with top-tier companies and our comprehensive career support contribute significantly to this high placement rate, affirming our commitment to student success in the dynamic field of Data Science.
What are the career paths for data scientists?
Data scientists have diverse career paths, spanning industries like tech, finance, healthcare, and more. They can specialize in various domains like machine learning, data analysis, or AI research. Roles include data analyst, machine learning engineer, AI researcher, or business intelligence analyst. Additionally, they may advance to managerial positions like data science manager or chief data officer, leading teams and strategies in data-driven organizations.
