Top 7 Data Science Courses in Coimbatore with Placements
Welcome to our list of the Top 7 Data Science Course Institutes in Coimbatore!
Coimbatore, sometimes shortened as Kovai, is one of the major metropolitan cities in the Indian state of Tamil Nadu. It is located on the banks of the Noyyal River and surrounded by the Western Ghats. Coimbatore is the second largest city in Tamil Nadu after Chennai in terms of population
Coimbatore is a major educational hub. The first school was established in 1931. The first college, Government Arts College, was opened in 1875. The first engineering college in the city, the Arthur Hope College of Technology, was started by G.D. Naidu in 1945 followed later by private engineering colleges PSG College of Technology, and Coimbatore Institute of Technology in the 1950s.
A major hub for manufacturing, education, and healthcare in Tamil Nadu, Coimbatore is among the fastest-growing tier-II cities in India. It houses more than 25,000 small, medium, and large industries with the primary industries being engineering and textiles. Coimbatore is called the “Manchester of South India” due to its extensive textile industry, fed by the surrounding cotton fields.
If you are looking for the best and most reliable information regarding Data Science courses in Coimbatore, then you have come to the right place, so let’s get started.
| Institute Rank | Name | Training Delivery Type | Offering Course Since | Fees | Placement Assistance |
| 1 | Digiperform- Digital Career Academy | Online | 2013 | INR 1,22,720 | 100% |
| 2 | Ether Infotech | Online & Offline | 2020 | INR 10,000 | Interviews Assured |
| 3 | DataMites | Online & Offline | 2018 | INR 68,900 | 100% |
| 4 | Black Board Learning | Online & Offline | 2016 | INR 87,500 | Interview Assured |
| 5 | Appin Technology | Online & Offline | 2013 | INR 45,000 | 100% |
| 6 | Imarticus Learning | Online & Offline | 2012 | INR 2,25,000 | 100% |
| 7 | 360 DigiTMG | Online | 2013 | INR 85,000 | 100% |
Think of Data Science as a digital detective. It’s like the superhero of information in the online world. Its job is to help us make sense of the tons of data we have. Picture a giant box of puzzle pieces – that’s the data. Data Science is a clever tool that puts those pieces together to reveal the bigger picture. It uses cool tools and math tricks to analyze and understand the information hidden in numbers, words, or pictures.
Now, why is this so important? Well, consider how much data we create every day – from social media posts to online shopping. Data Science is there to help companies and scientists make sense of all this information. It helps businesses figure out what customers like and want, making shopping easier for you.
It also helps doctors find patterns in health data, leading to better treatments and medicines. So, Data Science is like a superhero that helps us uncover the secrets hidden in our digital world. It makes our lives better by turning heaps of data into useful insights. The next time you wonder how your favorite app knows exactly what you want, give a shout-out to Data Science for making it happen!
1. Digiperform
Digiperform is the largest “Exclusive Digital Domain Specific” training provider in India. Our curriculum is designed and updated by the content panel of over 50 experts from across the digital marketing industry; combining the endorsements & suggestions of 450 knowledgeable corporates across Asia.
The curriculum has been created after surveying job requirements of over small and big digital marketing agencies and corporate houses with in-house digital marketing wings to provide hands-on training with a mix of practical, research, and assignments.
Why Choose Digiperform Online Data Science Course?
Come join our Data Science Training Program, the best in India, to start your journey in data science. You’ll get hands-on experience with over 75 projects covering things like Stats, Advanced Excel, SQL, Python Libraries, Tableau, Advanced Machine Learning, and Deep Learning. These projects are like real-life puzzles found in various industries such as healthcare, manufacturing, sales, media, marketing, and education. The training prepares you for more than 30 different job roles, getting you ready for a variety of exciting opportunities.
Data Science Online Course: Advantages
Taking an online course in Data Science is like going on a super cool learning adventure right from your comfy space. One big plus is flexibility – you get to decide when and where you learn. No need to rush to a classroom; you can even study in your PJs if you want! Plus, online courses often let you learn at your own speed. If you need more time on a tricky concept, no problem!
Another cool thing is accessibility. Thanks to the internet, you can connect with awesome teachers and resources from all over the world. It’s like having a virtual library right at your fingertips! Online courses also use interactive tools and videos, making learning way more fun and engaging than boring textbooks.
Saving money is another bonus. You don’t have to worry about travel expenses or buying expensive textbooks. You can become a Data Science whiz without spending too much. So, if you’re ready for an adventure in the world of data and numbers, an online Data Science course might be just what you’re looking for!
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 and Assignments
Major Projects
Customer Lifetime Value Calculation: The project involves calculating the customer lifetime value using SQL to understand the revenue generated by a customer over their lifetime.
Customer Churn Prediction: This project involves building a predictive model using SQL to identify customers who are likely to churn based on their behavior and transaction history.
Interactive Dashboard for E-Commerce Sales: The project involves creating an interactive dashboard using Tableau & SQL to analyze retail sales data, identify trends, and make data-driven decisions.
Customer Segmentation Dashboard: This project involves creating a customer segmentation dashboard using Tableau to identify customer groups based on demographics, behavior, and purchasing patterns.
Movie Recommendation System: The project involves building a movie recommendation system using Python and its libraries such as Pandas, NumPy, and Scikit-Learn. The recommendation system will suggest movies based on user preferences and ratings.
Sentiment Analysis on Twitter Data: This project involves analyzing Twitter data using Python and its libraries such as NLTK and TextBlob to perform sentiment analysis and understand the overall sentiment of a particular topic.
Visualizing COVID-19 Data: The project involves visualizing COVID-19 data using Python and its libraries such as Matplotlib, Seaborn, and Plotly to understand the impact of the pandemic on different countries and regions.
Visualizing Stock Market Data: This project involves visualizing stock market data using Python and its libraries such as Pandas, Matplotlib, and Bokeh to understand the trends and patterns in stock prices over time.
Airbnb Data Analysis: The project involves performing exploratory data analysis on Airbnb data to understand the patterns in the pricing, availability, and quality of Airbnb listings in different cities.
Bike Sharing Data Analysis: This project involves performing exploratory data analysis on bike sharing data to understand the usage patterns of bikes in different cities and identify factors that influence bike usage.
House Price Prediction: The project involves building a regression model using Python and its libraries such as Scikit-Learn to predict the prices of houses based on their features such as location, size, and amenities.
Credit Risk Prediction: This project involves building a classification model using Python and its libraries such as Scikit-Learn to predict the credit risk of loan applicants based on their credit history and other factors.
Time Series Forecasting for Sales Data: The project involves building a time series forecasting model using advanced machine learning algorithms such as ARIMA and LSTM to predict future sales trends and identify factors that influence sales.
Sentiment Analysis on Product Reviews: The project involves building a sentiment analysis model using NLP techniques such as Word Embeddings and Recurrent Neural Networks (RNN) to analyze product reviews and understand the sentiment of customers towards different products.
Segmentation using Deep Learning: This project involves using advanced deep learning techniques such as Fully Convolutional Networks (FCN) and U-Net to perform image segmentation and identify objects in images.
Machine Translation using Transformers: This project involves building a machine translation model using advanced deep learning techniques such as Transformers to translate text from one language to another.
Case Studies & Assignments:
- Healthcare Customer Feedback Analysis
- Management Teams Dashboard Creation
- Retail Store Sales Report Analysis
- Software Firm Employee Data Analysis
- Industrial Data Sets Classification & Comparison
- Charts & Graphs: Frequency Distribution Table, Pie-charts, Pareto Diagram, Histogram, Scatter Plots, Heatmaps, Bar Graphs and many More.
- Patient Disease Probability Analysis Using Healthcare Data
- Car Model & Menu Item Data Combination & Configuration Probability Analysis
- Manufacturing & Product Launch Data Classification & Analysis
- Customer Complaint Resolution Analysis Using Normal Distribution Curves
- Product Rating & Employee Productivity Analysis Usign Z-Score
- New Product Need Analysis Using Hypothesis Testing
- Inventory Management & Customer Segmentation Systems Using Vlook up & Hlook Lookup
- Sales Trend & Staffing Plan Creation using Pivot Tables
- Pricing Strategy & Financial Model Creation Using What if Analysis
- Sales & Operations Dashboard Creation
- Healthcare & Construction Reporting Automation Using Macros
- Retail Sales Opportunity Analysis Using PIVOT Charts
- Accounting Firm Statement Analysis Using Sparklines & Waterfall Chart
- FMCG Marketing Spend to Sales Revenue Impact Analysis Using Regression Analysis
- Transportation Pricing Model Using Regression Analysis
Data Science Placements
100% * Placement Assistance Dedicated Placement Cell To Help You Land Your Dream Job
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
They are a leading software training and placement company dedicated to empowering individuals with the skills they need to thrive in the ever-evolving world of technology. With their ISO 9001:2015 certification, they ensure that their training programs and placement services meet the highest standards of quality and effectiveness.
At Ether Infotech, they understand that the demand for skilled software professionals is constantly growing. To bridge the gap between industry requirements and the skills possessed by job seekers, they offer comprehensive training programs in a wide range of cutting-edge technologies. Their courses are meticulously designed and delivered by industry experts who bring their extensive knowledge and practical experience to the classroom.
Course Curriculum:
- Data Science Overview
- Data Analytics Overview
- Statistical Analysis and Business Applications
- Python: Environment Setup and Essentials
- Mathematical Computing with Python (NumPy)
- Scientific Computing with Python (Scipy)
- Data Manipulation with Python (Pandas)
- Data Visualization in Python
- Data Science with Python Web Scraping
Course Highlights:
- Enhance employability
- Industry-based Syllabus.
- Group activities like TED and active participation in Python communities to enhance the learnability of a student
- Interview Questions
- Video-based learning sessions apart from regular Python class
| Name | Data Science With Python Training |
| Course Duration | 2 Months |
| Website | www.etherinfotech.com |
| Address: | 35/4, 2ndFloor, Arputham Towers, Desabandhu Street, Ram Nagar, Coimbatore – 641009 Mob: 082205 71905 |
| Avg. Google Rating: | 5 |
| Offering DS Training in Coimbatore Since: | 2020 |
| Fees | INR 10,000 |
| Branches in India: | Coimbatore |
| Flagship Course Names: |
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| Exclusive Data Science Institute: | Yes |
| Training Delivery Model | Online & Offline |
DataMites in Coimbatore is a top player in the category of Computer Software Training Institutes in Coimbatore. This well-known establishment acts as a one-stop destination servicing customers both locally and from other parts of Bangalore. Throughout its journey, this business has established a firm foothold in its industry.
The belief that customer satisfaction is as important as their products and services has helped this establishment garner a vast base of customers, which continues to grow by the day.
Course Curriculum:
- Data Science Foundation
- Python Essentials
- R Language Essentials
- Maths for Data Science
- Statistics for Data Science
- Data Preparation with Pandas
- Visualization with Python
- Machine Learning Associate
- Advanced Machine Learning
- SQL for Data Science
- Deep Learning – CNN Basics
- Tableau Associate
- ML Model Deploy – Flask API
- Big Data Foundation
- Data Science Project Execution
Course Highlights:
- IABAC® & NASSCOM® Certification
- 700 Learning Hours
- 120-Hour Classroom Sessions
- 25 Capstone & 1 Client Project
- Cloud Lab Access
- Internship + Job Assistance
| Name | Data Science Courses |
| Course Duration | 6 Months |
| Website | www.datamites.com |
| Address: | 2, Greycoders, Vinayagar Koil St, Kongu Nagar Extension, Krishnaswamy Nagar, Sowripalayam Pirivu, Ramanathapuram, Tamil Nadu 641045 Call: 1800-313-3434 |
| Avg. Google Rating: | 5 |
| Offering DS Training in Coimbatore Since: | 2018 |
| Fees | INR 68,900 |
| Branches in India: | Pune Maharashtra, Kerala, Kolkata, Ahmedabad, Coimbatore |
| Flagship Course Names: |
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| Exclusive Data Science Institute: | Yes |
| Training Delivery Model | Online/Offline |
They offer Data Science Analytics Certification courses to working professionals and students. Founded in 2016, and renowned for complete hands-on sessions, they have trained more than 3000+ students across Bangalore, Chennai, and Coimbatore.
Course Curriculum:
- Module 1: Begin with Excel
- Module 2: Advanced Excel
- Module 3: Visualization with Table
- Module 4: Advanced Business Intelligence
- Module 5: Descriptive Statistics
- Module 6: Inferential Statistics
- Module 7: Exploring Data Analysis
- Module 8: Machine Learning -Regression
- Module 9: Machine Learning -Classification
- Module 10: Data pre-processing
- Module 11: Advanced Machine Learning
- Module 12: Deep Learning
- Module 13: Data Engineering
- Module 14: Putting it all together
- Module 15: Visualization with Power BI
- Module 16: Advanced BI
Course Highlights:
- 8+ Interview Calls
- 1 Month of dedicated interview preparation
- Project Portfolio for Interviews
- ATS enabled resume-building
- Mock interviews with full feedback
- Complete Hands-on Session
- Bootcamp style Teaching
- 32+ Industry Projects
- No Cost EMI option
- 14+ Tools and packages
| Name | Data Science Course |
| Course Duration | 5 Months |
| Website | www.blackboardlearning.in |
| Address: | 5th floor, Mayflower Valencia, Avinashi Road, Peelamedu, Coimbatore – 641004 Phone:8248984562 |
| Avg. Google Rating: | 5 |
| Offering DS Training in Coimbatore Since: | 2016 |
| Fees | INR 87,500 |
| Branches in India: | Bangalore, Chennai, Coimbatore |
| Flagship Course Names: |
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| Exclusive Data Science Institute: | Yes |
| Training Delivery Model | Online & Offline |
Appin Technology Coimbatore, a division of Ether Services, is the leading and most reputable software training institute in Coimbatore. Since its establishment in 2013.
They have been at the forefront of providing comprehensive Software Training, Product Development, and IT Consulting solutions to individuals and organizations seeking to excel in the field of technology.
Over the years, they have successfully trained and transformed the careers of thousands of students, empowering them with the skills necessary to excel in the dynamic IT industry.
Course Curriculum:
- Statistics Essentials for Analytics
- Data Science Overview
- Data Analytics Overview
- Statistical Analysis and Business Applications
- Data Visualization in Python using Matplotlib
- Python: Environment Setup and Essentials
- Mathematical Computing with Python (NumPy)
- Scientific computing with Python (Scipy)
- Data Science with Python Web Scraping
- Data Manipulation with Python (Pandas)
- Machine Learning with Python (Scikit–Learn)
- Natural Language Processing with Scikit-Learn
- Python integration with Hadoop, MapReduce, and Spark
| Name | Data Science With Python |
| Course Duration | 3 Months |
| Website | www.appincoimbatore.com |
| Address: | 144, Sengupta Street, Near Hotel City Towers Ram Nagar, Coimbatore – 641009 Mob: 095972 71533 |
| Avg. Google Rating: | 5 |
| Offering DS Training in Coimbatore Since: | 2013 |
| Fees | INR 45,000 |
| Branches in India: | Coimbatore |
| Flagship Course Names: |
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| Exclusive Data Science Institute: | Yes |
| Training Delivery Model | Online & Offline |
Founded in 2012, Imarticus Learning Institute is known for helping students grow in many ways. They focus on making students better in everything, like building skills and getting training. The institute is good at teaching technical stuff.
They have programs for people who want to learn new technical skills and get certifications to help their careers. Imarticus Learning Institute offers certification programs, professional degree programs, and postgraduate programs in Finance, Analytics, Technology, and Management.
Students can learn in different ways, like in classrooms or online, and they have good teachers. Imarticus Learning Institute gives students lots of choices for how they want to learn, including regular classes, online learning, and personalized mentorship programs.
Course Curriculum:
- Foundation
- Core Track
- SQL
- Python Programming
- Statistics for Data Science
- Machine Learning
- Data Visualisation with Tableau and Power BI
- Specialization 1 – Advanced ML Track
- Specialization 2 – Data Analytics & ML Track
Course Highlights:
- KPMG India COE Organised Hackathons
- Live Learning Module
- Real-world Projects
- 100% Job Assurance
- Job-specific Curriculum
- Dedicated Career Services
| Name | Postgraduate Program In Data Science And Analytics |
| Course Duration | 11 Months |
| Website | www.imarticus.org |
| Address: | Meena Highrise, No 110 to 113 West Thiruvengadasamy Road, R S Puram Opp to FIITJEE Institute and, near Nilgiris Supermarket, Coimbatore, Tamil Nadu 641002 Mob: 099537 81020 |
| Avg. Google Rating: | 4 |
| Offering DS Training in Coimbatore Since: | 2012 |
| Fees | INR 2,25,000 |
| Branches in India: | Mumbai, Bangalore, Pune, Delhi, Gurugram, Jaipur, Hyderabad, Chennai, Lucknow, Cochin, Coimbatore |
| Exclusive Data Science Institute: | Yes |
| Flagship Course Names: |
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| Training Delivery Model | Online /Offline |
360DigiTMG is a top choice for many industries worldwide and a great place for people who want to learn. It’s known for making a big difference in people’s careers by offering excellent learning experiences. What makes 360DigiTMG special is that it stands out from the others. It has a strong global presence and provides top-notch training, with its main headquarters located in India.
Course Curriculum:
- CRISP-DM – Project Management Methodology
- Exploratory Data Analytics (EDA) / Descriptive Analytics or Descriptive Statistics
- Statistical Data Business Intelligence and Data Visualization
- Plots & Inferential Statistics
- Probability Distributions (Continuous & Discrete)
- Hypothesis Testing – The ‘4’ Must Know Hypothesis Tests
- Data Mining Supervised Learning – Linear Regression, OLS
- Predictive Modeling – Multiple Linear Regression
- Lasso and Ridge Regressions
- Logistic Regression – Binary Value Prediction, MLE
- Multinomial Regression and Ordinal Regression & more
Course Highlights:
- 180+ Hours Online + Classroom Sessions
- 150+ Hours of Practical Assignments
- 2 Capstone Projects
- Certified
- 100% Placement Assistance
- Live Free Webinar
- 24/7 Support
| Name | Professional Course in Data Science & AI |
| Course Duration | 6 Months |
| Website | www.360digitmg.com |
| Address: | 1st Floor, Lotus Building, Old Balasubramaian Street, NSR Rd, Saibaba Colony, Tamil Nadu 641038 Phone: 097900 10308 |
| Avg. Google Rating: | 4 |
| Offering DS Training in Coimbatore Since: | 2013 |
| Fees | INR 85,000 |
| Branches in India: | Pune, Hyderabad, Bangalore, Chennai, Tamil Nadu |
| Flagship Course Names: |
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| Exclusive Data Science Institute: | Yes |
| Training Delivery Model | Online /Offline |
Who should learn Data Science in Coimbatore?
Well, anyone curious about the magic behind data and eager to explore the world of numbers is welcome! If you’re a student keen on discovering the secrets hidden in data or a working professional looking to boost your career with valuable skills, Data Science is for you. Coimbatore’s Data Science courses cater to beginners and those already in the tech field, offering a chance to unravel the mysteries of data analysis. Whether you’re from a business background, a computer whiz, or just someone excited about learning new things, Data Science in Coimbatore is open to all. So, if the idea of turning data into valuable insights sparks your interest, it’s time to jump into the exciting world of Data Science in Coimbatore!
Why should you study Data Science?
Learning Data Science is like gaining a superpower to reveal cool insights from heaps of information. Think about making smarter choices, predicting trends, or coming up with innovative solutions – that’s the special magic of Data Science.
Whether you’re naturally curious, love solving problems, or want better job chances, learning Data Science gives you important skills for today’s digital world. It’s not just about numbers; it’s about grasping how the world works and making a real difference. So, if you’re excited about an awesome journey of discovery, studying Data Science is your key to opening up tons of opportunities!
Career Scope in Data Science in Coimbatore
Thinking about the job opportunities in Data Science in Coimbatore? Well, it’s like having a treasure chest full of exciting career paths! In simple terms, Data Science is a hot field that opens doors to cool jobs. Coimbatore’s job market is buzzing with opportunities for Data Science enthusiasts.
Picture this: Companies in Coimbatore are on the lookout for Data Scientists who can turn raw data into useful information. Whether it’s predicting trends, solving complex problems, or helping businesses make smart decisions, Data Scientists are like the superheroes of the job world here.
Not just that, there’s a demand for Data Analysts too. They dive into data, find patterns, and help businesses understand what customers want. It’s like being a detective for numbers!
And guess what? Big companies in Coimbatore are eager to hire Data Engineers who can build and manage the systems that handle all this data magic. It’s a bit like being the wizard behind the scenes.
So, if you’re keen on a career that’s both exciting and in demand, exploring Data Science in Coimbatore could be your ticket to a world of awesome job opportunities!
Mastering Data Science Tools
“Explore the realm of data science through Digiperform’s ‘Mastering Data Science Tools’ course. Delve into Python, R programming, and cutting-edge machine learning techniques to enhance your capacity in interpreting valuable data insights. Acquire hands-on proficiency using pertinent industry tools, preparing to tackle authentic data predicaments. Enhance your skills and widen career opportunities in the field of data science with Digiperform’s thorough and applied curriculum.”
Data Science Salaries for Freshers in Coimbatore
For newbies entering the field of Data Science in Coimbatore, the salary scene is looking pretty good! If you’re just starting out, companies in Coimbatore appreciate the fresh perspective you bring to the table. As a fresher in Data Science, you can anticipate a decent salary that reflects your knowledge and eagerness to explore the data world. The demand for data skills is on the rise, and Coimbatore, with its growing tech scene, offers promising opportunities. So, if you’re enthusiastic about delving into the realm of data and happen to be in Coimbatore, not only will you get to work on interesting projects, but you’ll also enjoy a salary that acknowledges your potential and sets you on a rewarding career path.
Current Job Openings in Data Science in Coimbatore
Coimbatore is a hotspot for Data Science job openings! Companies in various sectors are on the lookout for talented individuals skilled in data analysis, machine learning, and more. Whether you’re a seasoned pro or just starting your career, Coimbatore’s job market has something for everyone.
Check out online job portals, and company websites, or connect with local tech communities to explore the latest opportunities. From exciting startups to established firms, Coimbatore’s growing demand for Data Science professionals means a wealth of job possibilities for those ready to dive into the world of data-driven careers!
You can refer to these websites: Naukri.com, Linkedin.com, Indeed.com and many more.
FAQs: Data Science Course
Will I get a certificate after the completion of the course?
Yes. You will receive a certificate or Diploma from your training institute after the completion of the course.
Do data scientists work from home?
The field of Data Science is one of the most popular occupations in which work can be done from home. This field is no stranger to remote work. Jobs in the field of Data Science are considered the most remote-friendly jobs.
Can a data analyst become a data scientist?
Yes! Although data analytics and data science are two distinct career paths, the skills used in data analysis can serve as an excellent starting point for making a career in data science.
Is data science a good career?
Yes, data science is among the best careers that offer tremendous opportunities for advancement in the future. It is already in high demand, its salaries are competitive, and its perks are numerous which is why Data Scientist has been called “the most promising career” by LinkedIn.
