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Data Science Course in Coimbatore

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  • Beginner & Advanced Level Classes
  • Top MNC Interview Question Coverage
  • Delivered by 9+ Years of Data Science Certified Expert
  • Affordable Fees and Industrial Expert-designed Curriculum
  • Access to Trendy Projects and Advanced Research Resources
  • Next Data Science Batch to Start This Week – Enroll Your Name Now!

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Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session


Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session


Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session


Weekend Fasttrack

(09:00 AM - 02:00 PM)

(Class 4:30Hr - 5:00Hrs) / Per Session

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Get Our Expert Data Science Course

  • Our Data science course equips learners with crucial skills in data handling, insight extraction, and data-driven decision-making, covering subjects like statistics, programming, data analysis, and machine learning.
  • Our course covers data collection, visualization, statistical analysis, machine learning, and big data technologies, with students studying programming languages like Python and R.
  • Our Data science course offers a range of formats, including in-person classrooms, online courses, and bootcamps, allowing students to choose the one that best suits their schedule and learning preferences.
  • ACTE's Data science course emphasizes hands-on experience, involving real-world tasks and projects where students use datasets to solve problems and learn valuable skills.
  • Our trainers are frequently highly experienced professionals in the field of data science. They are in the position of giving lectures, conducting practical classes, and counselling students.
  • Our courses provide placement aid or corporate partnerships for data science students, offering resume-writing classes, interview training, and career advice with potential placement prospects.
  • We offer chances for networking with teachers, fellow students, and business experts. Finding employment prospects and staying current with industry trends can both benefit from networking.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

Course Objectives

  • Huge Demand
  • Employment Possibilities
  • Professional Development
  • Versatility
  • Networking
  • Data-Driven Decision-Making

Having a strong background in statistics and maths is beneficial for understanding the mathematical concepts and methods used in data science. Familiarity with topics such as algebra, calculus, probability, and statistical analysis provides a strong basis for data science coursework.

A Data Science course equips individuals with the skills to analyze vast datasets, making data-driven decisions and fostering innovation. This expertise in data analysis, machine learning, and visualization can solve problems, predict trends, and contribute to various industries. This course offers employment opportunities and a significant impact in a data-abundant world.

  • Data Visualization
  • Data Preprocessing
  • SQL and Database Knowledge
  • Exploratory Data Analysis
  • Programming Skills.
  • Practical Projects
  • Collection and Cleaning of Data
  • Machine Learning Models
  • Version Deployment
  • Exploratory Data Analysis
  • A/B Testing

  • Data preprocessing and cleaning
  • Learning Programming for Data Science
  • Time series analysis
  • Natural Language Processing (NLP)
  • Big Data Analytics
  • Evaluating ethical issues
  • Project capstone.

  • Data Scientist
  • Data Analyst
  • Quantitative Analyst (Quant)
  • Data Engineer
  • Machine Learning Engineer

What is the scope of a Data science course?

A Data Science course covers a wide range of topics, expanding across industries as data science becomes increasingly significant. Companies across all sizes and industries require skilled data scientists to guide their business strategies, benefiting from data-driven decision-making advantages.

Is it easy to learn Data science?

Learning data science requires a committed effort, integrating statistics, programming, and domain expertise. It requires practice, critical thinking, and ongoing learning to efficiently analyze complex data and produce insightful conclusions.

Where is Data science utilized?

Data scientists are highly sought-after professionals across a wide range of industries. Here are some of the industries that frequently hire data science professionals are Finance, Banking, Healthcare, Technology, E-commerce, Marketing, and Advertising

Which tools does data science employ?

  • Matplotlib
  • R
  • Pandas
  • TensorFlow and PyTorch
  • OpenRefine
  • Hadoop
  • Tableau
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A Comprehensive Overview of Data Science

Data science is a field of study that covers statistics, machine learning, data visualisation, programming languages (such as Python or R), data manipulation, and interactive data analysis. Online training courses provide access to curated datasets and tools used in the industry, allowing learners to practice their skills by working with real data and using popular data science tools and software. Course trainers for data science are experienced professionals who have expertise in the field of data science and its subdomains, providing guidance and insights based on their practical industry experience.



Additional Info

Career Scope for Data Science

The career scope for data science is highly promising and continues to grow rapidly as organizations across industries recognize the value of data-driven insights. Here are some key aspects that highlight the career scope for data science professionals:

  • Rapidly Expanding Sector: The field of data science is expanding rapidly, and there is a growing need for qualified personnel.
  • Various Industries: Data science has applications in various industries, including finance, healthcare, e-commerce, marketing, and more.
  • Ethics-Related Matters: Professionals in data science are essential in resolving ethical issues related to bias, security, and privacy of data.
  • Profitable Salaries: Due to a shortage of qualified people and the value data scientists provide to organisations, they frequently charge hefty wages.
  • Wide Range of Roles: Data analysts, data engineers, machine learning engineers, and data scientists are just a few of the employment types available in data science.
  • Frequent Innovation: Data science is a dynamic discipline that continually evolves, creating great chances for experimentation and innovation.
  • High Demand: Data scientists are in high demand since there is a severe shortages of competent candidates.

Roles and Responsibilities of Data Science Engineer

  • Data science engineers gather and collect data from multiple sources, including databases, APIs, and external datasets.
  • To gain insight and analyse the patterns, trends, and correlations present in the data, data science engineers do exploratory data analysis.
  • In order to analyse the data, find relevant variables, and extract useful data, they make use of statistical techniques, visualisation tools, and machine learning algorithms.
  • Data science engineers develop predictive models and machine learning algorithms using techniques such as regression, classification, clustering, and recommendation systems.
  • They work closely with data scientists and domain experts to understand business requirements and translate them into mathematical models.
  • They also evaluate and select appropriate algorithms, tune model parameters, and validate model performance.
  • Data science engineers set up models into production environments after they've been created and make sure they are fully integrated with current systems.

Trends and Techniques used in Data Science

Data science is a dynamic field that continually evolves with advancements in technology and the availability of vast amounts of data. Here are a few data science trends and methods now in use:

  • Deep learning and machine learning utilize data-driven techniques like supervised, unsupervised, reinforcement learning, and neural networks for prediction and decision-making.
  • Big data analytics is crucial in data science, utilizing tools and frameworks to process, store, and analyze complex datasets for organizations.
  • NLP combines computers and human language, enabling machines to understand, interpret, and generate human language for applications like chatbots and voice assistants.
  • AutoML streamlines machine learning model development and deployment by automating tasks like feature engineering, selection, tuning, and deployment.
  • Explainable AI provides machine learning model insights, transparency, and accountability through techniques like feature importance analysis and rule extraction.
  • Reinforcement learning trains agents to make sequential decisions in dynamic environments, rewarding and penalizing undesirable behaviors.

Organizational Benefits of Data Science

Numerous organizational advantages provided by data science can have a big impact on how businesses operate and how decisions are made. Here are a few of the main advantages of data science for organizations:

  • Data science contributes to operational efficiency and cost savings by streamlining corporate processes, automating repetitive jobs, and identifying inefficiencies.
  • Data science enables businesses to better understand their client's needs and habits through analysis of customer data, resulting in personalized marketing and improved customer experiences.
  • Targeted marketing efforts, individualized product recommendations, and more successful sales tactics are made possible by data science.
  • Organizations can use data science to analyze data in real-time, which enables speedy decision-making and prompt reactions to market developments.
  • Data science may streamline supply chain operations by enhancing demand forecasts, logistics, and inventory control.
  • Data science makes it possible to continuously monitor and analyze data, which leads to constant improvements in company plans and procedures.
  • Data science assists in risk assessment and management for a variety of corporate activities, including supply chain management and financial investments.

Tools used for Data Science

Data science encompasses a wide range of tasks, from data acquisition and preprocessing to modeling and visualization. Various tools and technologies are used to facilitate these tasks. Here are some commonly used tools in data science:

  • Python: Python provides an extensive ecosystem of frameworks and libraries, including pandas, scikit-learn, tensorflow, and PyTorch.
  • R: It provides a comprehensive set of packages and libraries for data manipulation, visualization, and statistical modeling.
  • SQL: It allows data scientists to extract, manipulate, and query data from databases using commands like SELECT, INSERT, UPDATE, and JOIN.
  • Apache Hadoop: Apache Hadoop, which includes elements like HDFS and MapReduce, is a widely used platform for the distributed analysis and storage of huge data.
  • Apache Spark: It supports various programming languages and offers libraries for data manipulation, machine learning (MLlib), and graph processing (GraphX).
  • Jupyter Notebooks: Jupyter Notebooks are interactive web-based environments that enable document creation as well as sharing for data scientists containing live code, and explanatory text.
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Key Features

ACTE Coimbatore offers Data Science Training in more than 27+ branches with expert trainers. Here are the key features,

  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.


Syllabus of Data Science Course in Coimbatore
Module 1: Data Science Basics
  • Introduction to Data Science
  • Significance of Data Science
  • R Programming basics
Module 2: Python Fundamentals
  • Python Introduction
  • Indentations in Python
  • Python data types and operators
  • Python Functions
Module 3: Data Structures and Data Manipulation
  • Data Structures Overview
  • Identifying the Data Structures
  • Allocating values to the Data Structures
  • Data Manipulation Significance
  • Dplyr Package and performing different data manipulation operations
Module 4: Data visualization
  • Introduction to Data Visualisation
  • Various kinds of graphs, Graphics grammar
  • Ggplot2 package
  • Multivariant analysis by using geom_boxplot
  • Univariant analysis
  • Histogram, barplot, multivariate distribution, and density plot
  • Bar plots for the categorical variables through geop_bar() and the theme() layer
Module 5: Statistics
  • Statistics Importance
  • Statistics classification, Statistical terminology
  • Data types, Probability types, measures of speed, and central tendency
  • Covariance and Correlation, Binary and Normal distribution
  • Data Sampling, Confidence, and Significance levels
  • Hypothesis Test and Parametric testing
Module 6: Introduction to Machine Learning
  • Machine Learning Fundamentals
  • Supervised Learning, Classification in Supervised Learning
  • Linear Regression and mathematical concepts related to linear regression
  • Classification Algorithms, Ensemble Learning techniques
Module 7: Logistic Regression
  • Logistic Regression Introduction
  • Logistic vs Linear Regression, Poisson Regression
  • Bivariate Logistic Regression, math related to logistic regression
  • Multivariate Logistic Regression
  • Building Logistic Models
  • False and true positive rate
  • Real-time applications of Logistic Regression
Module 8: Random Forest and Decision Trees
  • Classification Techniques
  • Decision Tree Induction Algorithm
  • Implementation of Random Forest in R
  • Differences between classification tree and regression tree
  • Naive Bayes, SVM
  • Entropy, Gini Index, Information Gain
Module 9: Unsupervised learning
  • Clustering, K-means clustering, Canopy Clustering, and Hierarchical Clustering
  • Unsupervised learning, Clustering algorithm, K-means clustering algorithm
  • K-means theoretical concepts, k-means process flow, and K-means implementation
  • Implementing Historical Clustering in R
  • PCA(Principal Component Analysis) Implementation in R
Module 10: Denial-of-Service
  • DoS/DDoS Concepts
  • Botnets
  • DoS/DDoS Attack Techniques
  • DDoS Case Study
  • DoS/DDoS Countermeasures
Module 11: Natural Language Processing
  • Natural language processing and Text mining basics
  • Significance and use-cases of text mining
  • NPL working with text mining, Language Toolkit(NLTK)
  • Text Mining: pre-processing, text-classification and cleaning
Module 12: Mathematics for Data Science
  • Numpy Basics
  • Numpy Mathematical Functions
  • Probability Basics and Notation
  • Correlation and Regression
  • Joint Probabilities
  • Bayes Theorem
  • Conditional Probability, sum rule, and product rule
Module 13: Scientific Computing through Scipy
  • Scipy Introduction and characteristics
  • Integrate, Cluster, Signal, Fftpack, and Bayes Theorem
Module 14: Python Integration with Spark
  • Pyspark basics
  • Uses and Need of pyspark
  • Pyspark installation
  • Advantages of pyspark over MapReduce
  • Pyspark applications
Module 15: Deep Learning and Artificial Intelligence
  • Machine Learning effect on Artificial Intelligence
  • Deep Learning Basics, Working of Deep Learning
  • Regression and Classification in the Supervised Learning
  • Association and Clustering in unsupervised learning
  • Basics of Artificial Intelligence and Neural Networks
  • Supervised Learning in Neural Networks, multi-layer network
  • Deep Neural Networks, Convolutional Neural Networks
  • Reinforcement Learning
  • Recurrent Neural Networks, Deep learning graphics processing unit
  • Deep Learning Applications, Time series modeling
Module 16: Keras and TensorFlow API
  • Tensorflow Basics and Tensorflow open-source libraries
  • Deep Learning Models and Tensor Processing Unit(TPU)
  • Graph Visualisation, keras
  • Keras neural-network
  • Define and Composing multi-complex output models through Keras
  • Batch normalization, Functional and Sequential composition
  • Implementing Keras with tensorboard
  • Implementing neural networks through TensorFlow API
Module 17: Restricted Boltzmann Machine and Autoencoders
  • Basics of Autoencoders and rbm
  • Implementing RBM for the deep neural networks
  • Autoencoders features and applications
Module 18: Big Data Hadoop and Spark
  • Big Data and Hadoop Basics
  • Hadoop Architecture, HDFS
  • MapReduce Framework and Pig
  • Hive and HBase
  • Basics of Scala and Functional Programming
  • Kafka basics, Kafka Architecture
  • Kafka cluster and Integrating Kafka with Flume
  • Introduction to Spark
  • Spark RDD Operations, writing spark programs
  • Spark Transformations, Spark streaming introduction
  • Spark streaming Architecture, Spark Streaming Features
  • Structured streaming Architecture, Dstreams, and Spark Graphx
Module 19: Tableau
  • Data Visualisation Basics
  • Data Visualisation Applications
  • Tableau Installation and Interface
  • Tableau Data Types, Data Preparation
  • Tableau Architecture
  • Getting Started with Tableau
  • Creating sets, Metadata and Data Blending
  • Arranging visual and data analytics
  • Mapping, Expressions, and Calculations
  • Parameters and Tableau prep
  • Stories, Dashboards, and Filters
  • Graphs, charts
  • Integrating Tableau with Hadoop and R
Module 20: MongoDB
  • MongoDB and NoSQL Basics
  • MongoDB Installation
  • Significance of NoSQL
  • CRUD Operations
  • Data Modeling and Management
  • Data Indexing and Administration
  • Data Aggregation Schema
  • MongoDB Security
  • Collaborating with Unstructured Data
Module 21: SAS Basics
  • SAS Enterprise Guide
  • SAS functions and Operators
  • SAS Data Sets compilation and creation
  • SAS Procedures
  • SAS Graphs
  • SAS Macros
  • Advance SAS
Module 22: MS Excel
  • Entering Data
  • Logical Functions
  • Conditional Formatting
  • Validation, Excel formulas
  • Data sorting, Data Filtering, Pivot Tables
  • Creating charts, Charting techniques
  • File and Data security in excel
  • VBA macros, VBA IF condition, and VBA loops
  • VBA IF condition, For loop
  • VBA Debugging and Messaging
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Hands-on Real Time Data Science Projects

Project 1
Natural Language Processing (NLP) Sentiment Analysis

Develop a sentiment analysis model using machine learning algorithms and NLP approaches to categorize text data like social media posts and customer reviews as positive, negative, or neutral.

Project 2
Image Classification with Convolutional Neural Networks (CNN)

Segmentation.Develop a CNN-based image classification system using datasets like CIFAR-10 or ImageNet, expanding its scope to include object detection and image segmentation.

Get the Impactful Data Science Course With Placement

Data Science course offers placement support, preparing students for tech industry roles through practical training and industry collaboration.

  • To give students the best chances to land satisfying jobs in the sector, ACTE offers Data Science course with placement support and counseling.
  • Placing a focus on practical tasks and abilities, our course equips students with the necessary expertise sought after by employers in the Data Science ecosystem.
  • A successful placement can open doors to various career opportunities in data science. Our organizations offer full-time positions to exceptional placement students upon completion.
  • We aggressively enable internship and job placement possibilities through industry partnerships and collaborations to jumpstart student's careers in the Data Science profession.
  • The adaptable training choices provided by ACTE include both online and in-person courses. The choice is yours about scheduling and learning preferences.
  • You can build your professional network by taking part in a placement programme with other Data Science professionals and subject matter experts.

Acquire Our Inventive Data Science Certification

All significant multinational corporations all around the world have accredited Acte Certification. We offer to freshmen as well as corporate trainees after the theoretical and practical sessions are over. ACTE's Data Science certification is recognized all around the world. If you can obtain top jobs with this skill set in renowned MNCs throughout the world, your resume's worth will increase. Only after completing our training and practice-based projects will the certification be granted. Sessions target novices as well as professionals.

Yes, obtaining a data science certification can considerably increase your chances of finding employment in the sector. Being credentialed in data science increases your marketability as a candidate for jobs by validating your skills and knowledge. Certifications are frequently highly valued by employers since they show that you are dedicated to lifelong learning and developing the abilities required for the position.

  • Validation and Reliability
  • Competitor advantage
  • Advancement in Career
  • Industry Acceptance
  • Worldwide Recognition
  • Data Analysis and Visualization Course
  • Machine Learning Course
  • Data Science with R Course
  • Data Science with SQL Course
  • Big Data and Data Engineering Course
  • Natural Language Processing (NLP) Course
  • Passing a data science course boosts income potential by demonstrating expertise and commitment to the field, as organizations pay premiums for qualified employees.
  • Data scientists are increasingly needed due to the increasing reliance on data-driven tactics, leading to a shortage of skilled workers with higher incomes and benefits.

If you have the time and motivation, you can pursue numerous data science certificates. Since data science is a heterogeneous topic, a wide range of certificates covering different facets of data analysis, machine learning, and related technologies are available. Obtaining several certificates can increase your knowledge of the industry and make you more appealing to companies.

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

Get Certified

a physical version of your officially branded and security-marked Certificate.

Get Certified

Enhance your Career With Our Data Science Trainers

  • Our data science trainers at ACTE are qualified individuals who work for illustrious companies and have at least nine years of business experience.
  • Our trainers at ACTE assist students in obtaining employment with significant MNCs like Facebook, Microsoft, Airbnb, Amazon, IBM, Google, and Ube.
  • Our Data Science trainers keep up with the most current trends and best practises, ensuring that students receive the most pertinent and recent training.
  • They have a thorough grasp of Data Science features and capabilities, which enables them to provide trainees with helpful guidance and in-depth real-world insights.
  • Due to the dedication of our Data Science specialists to the academic and professional development of its students, our institute will offer Data Science Course in Coimbatore.
  • Our experienced trainers provide students practical, hands-on training so they can use the Data Science services and tools themselves.

Data Science Course FAQs

Looking for better Discount Price?

Call now: +91 93833 99991 and know the exciting offers available for you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    ACTE Gives Certificate For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Data Science training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Data Science Course At ACTE?

  • Data Science Course in ACTE is designed & conducted by Data Science experts with 10+ years of experience in the Data Science domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Data Science batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Data Science. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
You can contact our support number at +91 93800 99996 / Directly can do by's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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      Job Opportunities in Data Science

      More Than 35% Of Developers Prefer Data Science. Data Science Is The Most Popular And In-Demand Programming Language In The Tech World.

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