Data Science Training in Kolkata | Best Data Science Certification Course
Home » Data Science & Ai Courses India » Data Science Training in Kolkata

Data Science Training in Kolkata

(5.0) 6987 Ratings 7089Learners

Live Instructor LED Online Training

Learn from Certified Experts

  • Newcomers & Excellent level Courses.
  • Most excellent Training toward conference Development Methods under Data Science.
  • Existence Path towards pupil Portal, Study guides, Videos & Top MNC Interview Topic.
  • Reasonable Payments beside Best curriculum Planned at Industrial Data Science Expert.
  • Performed over 9+ years as regarding Data Science Certified Specialist.
  • Following Data Science Batch to Start here a week– Register Your Sign Instantly!

aws training


INR 18000

INR 14000


INR 22000

INR 18000

Have Queries? Ask our Experts

+91-8376 802 119

Available 24x7 for your queries

Upcoming Batches


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

Hear it from our Graduate

Learn at Home with ACTE

Online Courses by Certified Experts

Play a design role and participate in IT companies.

  • The field of data science is a relatively new one, and this course examines the crucial tools and concepts needed, including machine learning, statistical analysis, and working with data at scale.
  • In the following sections, we will discuss the entire data science process as well as the various roles and skills required. Afterwards, you'll learn how to obtain data from different sources, including web APIs and pages scraped from the internet.
  • Learn how to work with data using tools like R, Python, the command line, and even spreadsheets.
  • A powerful data-analysis technique will be discussed as well. This class will cover a number of techniques for planning, performing, and presenting data science projects. These will get you started in data science and make you more efficient with the available data.
  • Throughout the course, you will be provided with the ultimate toolkit for a data science career. An overview of the field and its different career paths will be provided, such as Product Analyst, Data Engineer, Data Scientist, and many others.
  • Having the knowledge of the various options available will help you take full advantage of them. The course covers a wide range of topics, including probability, statistics, machine learning, product metrics, a variety of data sets, A/B testing, and market analysis, among others.
  • Several world-renowned technology companies will contribute to this course, including Amazon, Square, Facebook, Google, Microsoft, AirBnB, and more!
  • For each question in the course, detailed explanations and solutions will be provided. It also provides you with the opportunity to prepare for exams and serve as a reference while working.
  • You must be familiar with the following topics if you want to pass the interview.
  • With this curriculum, students will understand the subject better. Through our program, we help students prepare for job interviews and find employment with reputable companies.
  • Concepts: Data Science, significance of Data Science in today’s digitally-driven world, components of the Data Science lifecycle, big data and Hadoop, Machine Learning and Deep Learning, R programming and R Studio, Data Exploration, Data Manipulation, Data Visualization, Logistic Regression, Decision Trees & Random Forest, Unsupervised learning, Association Rule Mining & Recommendation Engine, Time Series Analysis, Support Vector Machine - (SVM), Naïve Bayes, Text Mining, Case Study.
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

This is How ACTE Students Prepare for Better Jobs


Course Objectives

This Data Scientist certification course combines online instructor-led sessions and self-paced study co-developed with IBM to provide comprehensive Data Science training. This certification program culminates in a capstone project that builds a real-world industrial product that incorporates all of the main concepts covered during the curriculum. The abilities covered in this course will assist you in becoming a Data Scientist.
  • Learn everything there is to know about data structure and data manipulation.
  • For data analysis, understand and use linear and non-linear regression models, as well as classification approaches.
  • Learn how to use supervised and unsupervised learning models including linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline to solve problems.
  • Use the SciPy package and its sub packages such as Integrate, Optimize, Statistics, IO, and Weave to perform scientific and technical computing.
The Data Science certification course is best suited for aspiring professionals with any educational background who have an analytical mindset, such as:
  • Professionals in Information Technology
  • Managers of Analytics
  • Analysts in the field of business
  • Professionals in Banking and Finance
  • Managers of Marketing
  • Managers of Supply Chain Networks
  • Beginners or recent bachelor's or master's degree graduates
Professionals who want to pass this Data Science certification course should have the following skills:
  • Basic statistical expertise is required.
  • Any programming language requires a basic grasp.
You will have the abilities necessary to get your ideal career in Data Science if you finish the Data Science certification course. Professionals with a background in data science are well-suited for the following positions:
  • Data Analyst
  • Data Scientist
  • Analytics Manager/Lead
  • Machine Learning Engineer
  • Statistical Programming Specialist
This Data Science certification course will teach you Python, R, and Scala computer languages, as well as data science technologies including Apache Spark, HBase, Sqoop, Hadoop, and Flume.
Companies are embracing digital transformation, and the increased reliance on data makes a data scientist job more appealing. Businesses are speeding up their digital activities, and data scientists will be in great demand shortly. Furthermore, given the existing skills shortage, firms are willing to offer data scientists greater wages. You may qualify for this rewarding job by taking Simplilearn's Data Scientist course.

Is a Data Science Course easy to learn?

Data science is a large area, and it is impossible to become an expert in it in six months or a year. To get started with data science, you'll need specific technical abilities as well as a fundamental understanding of programming and analytics tools. This Data Science course, on the other hand, covers all of the necessary topics from the ground up, making it simple to put your new abilities to use.

Who delivers this Data Science Certification Course?

Our highly trained Data Science instructors are all industry professionals with years of expertise in the field. Before they are qualified to train for us, they have gone through a thorough selection procedure that includes profile screening, technical examination, and a training demo. We also make certain that only trainers with a good alumni rating stay on our faculty.

What are the topics covered as a part of Data Science?

Machine Learning, K-Means Clustering, Decision Trees, Data Mining, Python Libraries, Statistics, Scala, Spark Streaming, RDDs, MLlib, Spark SQL, Random Forest, Nave Bayes, Time Series, Text Mining, Web Scraping, PySpark, Python Scripting, Neural Networks, Keras, TFlearn, SoftMax, Autoencoder, Restricted Boltzmann Machine, LOD Expressions, Tableau Desktop will be covered

Are data science certificates worth it?

With data science becoming increasingly important to many organizations' overall goals, it's worth considering if data science certifications are required to work as a data scientist. In other words, it's a profession that necessitates a wide range of abilities (and, depending on the company and position, a lot of experience).

Which certification is best for data science?

  • Azure AI Fundamentals is a Microsoft Certified program.
  • Azure Data Scientist Associate is a Microsoft certification.
  • SAS Certified AI & Machine Learning Professional, Open Certified Data Scientist (Open CDS).
  • SAS Big Data Professional certification.
  • SAS Data Scientist certification.
Show More

Overview of Data Science Training in Kolkata

The data studies are study of physical reactions, like biological science, of biological science. Data is real, data has real properties, and if we are to work on them we have to study them. Data science includes data and certain signsIt is not an event, it is a process. This Data Science Training in Kolkata has the process is to use data to understand and understand too many different things. Let us assume if you have a problem model or explanation, and you try to validate your data with that explanation or model.They are the ability to uncover (or abstract) the insights and trends behind data. It is by translating information into a storey. Use storytelling for insight. And you can choose a company or institution strategically with this insight.

We can also define data science as a field that deals with processes and systems in which data is extracted, whether data is unstructured or structured, from various forms and resources.In the definition and names were developed as professors, IT professionals and scientists examined the curriculum of statistics, and they thought it better to name it as data science and then as data analytics.

Additional Info

But what is data science the world's largest question and confusion?

I would see data science as one, and I would find solutions to questions they are exploring from one to many attempts to work with data. In summary, we can say that it concerns much more data than science. You are exploring it according to your own needs and the exercise of analysing your data, trying to obtain some answers or to fulfil the needs of society through your data explored, manipulated and exercised – it is data science. You are curious about working with and manipulating the information according to your needs.

Today, data science is relevant, as millions of data are available on single or single data. We have not used the absence of data to worry. We now have tonnes of information. We had no algorithms defined in the past, now we have algorithms. The software in the past wasn't accessible by all, because it was too costly, so only big-bucks industries can use it but it is now free and open source. Because the storages are also very costly and available for a split cost now, it allows us to get billions of data sets for a very low cost. We don't think we could store a large amount of data in the past. The Internet connectivity was also not common and was not too expensive. Therefore it is all cheap, all available, everything ubiquitous and here, the tools for working with data, data variability, data storage, data analysis and last and most important connectivity! No better time than now to be a data scientist.

Career Path in Data science :

Data science is currently considered one of industry's most lucrative jobs. Data science jobs show only signs of growth with numerous openings across all sectors. As companies are increasingly engaged in data science, companies are employing hordes of data scientists. However the demand gap for data science jobs compared to applicants is only expanding although India is a pioneer in technological education and research.70 percent of jobs in this sector currently cover data scientists with less than five years of experience in analytics in the analytical ecosystem.

A data scientist's career path is difficult for various reasons to trace. Most management at the medium and high-level levels with over 10-15 years of experience began with software or coding designations, because the industry was not developed enough to include a data scientist's designation. But now things are changing, and the next generations of data scientists will have a clearer understanding of their careers.

Job Position :

    1. Data Scientist :

    The creme de la créme is in any company a "Data Scientist." That's why professionals are most popular nowadays for this designation. This designation is used by many companies as it is easy to search and apply for aspirants. For the same purpose, other companies use designations such as "business intelligence expert" or "market analyst."

  • The role of a data scientist : "a unique mix of capabilities which can both open up data insights and tell a wonderful storey via the data" is defined by the American mathematician and computer specialist DJ Patil. Data scientists also have to develop machine learning models for prediction in modern workplaces, find patterns and trends in data, view data, and even pitch marketing approaches.

  • Skillset : statistics, math, data modelling, programming of Python or R, Additional abilities: Business skills, Visualization/BI, presentation capability. Business acumen.

  • Company ladder : The ladder would look like the following for a datologist / IT expert / market analyst. It is to be observed, however, that organisations, according to their convenience or their corporate structure, can rename certain appointments. A "lead data scientist" in certain organisations, for example, can be called a "main data scientist."

  • 2. Data Analyst :

    Organizations normally use this designation to report that more technical knowledge is involved in this role. Some of its synonyms are 'professional analysts' or 'business analysts.

  • Role : The role of a data analyst is based on company data, which can then be used by the C-suite for action. The fact that your projects usually change from time to time is another interesting fact about data analysts. Thus, the marketing department can be operated on by a data analyst for 3 months, and production may take the next one.
  • Skillset : Python or R, Tableau Data Modeling. Additional competencies: acumen of business, competency in database, visualization/BI, skills in presentation.
  • Corporate Leadder : the ladder of a professional/business analyst for a data analyst would look like the following. It must be noted, however, that this name also offers the flexibility to move laterally to more specific roles and niches.

  • 3. Data Engineer :

    Any large organisation has a data engineer as its backbone. In general, companies hire data engineers to channel their talents for the development of software. The Data Architect and the Quantitative Analyst are synonymous with some of its roles. "

  • Role : This role requires a deep knowledge of programming skills as a data engineer works with the core data infrastructure of the organisation. A data engineer is responsible for the construction of data pipes and the correction of the data flow in most organisations, so that information is received from the relevant Departments.
  • Knowledge set : management of database, cleaning of data, programming Python or R, Hadoop. Other competencies: business acumen, skills in database cleaning, visualization/IB, skill presentation.
  • Corporate lead : The corporate ladder would look like something like the following for a data engineer / data architect / quantitative analyst. Since it is more central and niche to the organisation, side movement is unusual. This job is, however, the most difficult to lay off for the same reason.

  • 4. Business Intelligence Developer :

    A developer of business information is a kind of jack of all businesses in any organisation which must essentially have a strong understanding of the fundamental elements of analysis and of the IT department. The "systems analyst" and "machine learning engineer" are among his synonymous roles.

  • Role : The role of a computer scientist has a great deal of overlaps with key features such as data science, programming and data architecture. This is not just analytical but technical, and calls for advanced knowledge of every popular technology learning.
  • Skillset : programming of Pythons or R, Hadoop, modelling, Notebook, Github, modelling of data.Additional skills: Accurate business, Visualization/BI
  • Career Ladder : A corporate ladder would look something like this for a computer engineer/system analyst/machine learning engineer. Because this role is relevant for nearly every other sector, notably digital and emerging technology, the lateral movement in the organisation also has a great opportunity.

Industry Path in Data Science :

Data science allows dealers to influence our buying practises, but the importance of data collection goes far beyond that. Data science can enhance public health by wearable trackers, which motivate people to adopt healthier habits and alert people to potential health challenges. Data may also enhance diagnostic accuracy, speed up the finding of treatments for certain diseases, and even stop a virus spreading. when the outbreak of Ebola virus reaches West Africa, scientists could track the disease's spread and predict the areas most vulnerable to the disease. These data have been used to prevent health officials from getting into the world before the outbreak. These data helped health officials to cope with the outbreak and prevent a global epidemic. In most industries, data science has critical applications. For example, farmers use data for effective food growth, food suppliers to cut food waste and non-profit organisations to boost fund-raising efforts and forecast funding needs. For example, farmers use data to reduce food waste. Economist and Freakonomics author, said in a lecture that CEOs are aware of the importance of Big Data but have no appropriate teams at their disposal to perform these skills.

"I really still believe that combining collaboration with corporate big data and randomising [...] will be at the heart of the economics and other social science." Pursuing a career in data science is an intelligent move, not only because it is trendy and well worthwhile, but because data can well be the centre of interest for the whole economy. In virtually every job – not only in technology – data science experts are needed. Actually, only one-half of a million employees are employed by the five largest tech companies — Google, Amazon, Apple, Microsoft, and Facebook. However, advanced education is generally necessary to break through to these highly-paid, on-demand roles. "Data scientists receive high educational qualifications–88 percent have at least a master's and 46 percent have a PhD–with remarkable exceptions, the profound knowledge required to be a data scientist is often very strongly educated," reports KDnuggets, a leading site on the Big Data.

Data Scientists are in Constant Demand :

Schedlbauer concludes "There is a clear need for professional professionals to understand a business requirement, to develop a data-dynamic solution and then to implement that solution," although work on information sciences will probably be automated over the next 10 years. Almost all fields, from state security to dating applications, require data science experts. In order to successfully serve their customers million enterprises and government departments rely on big data. Careers in data science are highly requested and this trend will not soon slow, if ever.There are a number of ways you can prepare to take on these challenging but exciting roles if you want to break into the field of data science. Maybe most importantly, by demonstrating your expertise and previous working experience, you will need to convince future workers. One way to build these skills and experience is to conduct an advanced degree in your field of interest.

For example, the University of Northeastern offers Masters in data science and data analytics to develop the skills employers seek. Both programmes also offer students a chance to participate in cooperatives and experiential learning experiences, so that they can build practical experience before graduation. Once factors such as your personal background, interest and career aspirations are taken into consideration, you can determine which degree programme is right for you and take the next step in achieving your goals.

Advantages of Data Science :

Data science's different advantages are :

1. This is at the request :

There is a high demand for data science. There are many opportunities for prospective job seekers. It is Linkedin's most rapidly growing job and will generate 11.5 million jobs by 2026. Data Science is therefore a highly employable sector.

2. Position abundance :

Very few people have the necessary skills to become a full data scientist. In comparison with other sectors of IT, data science is thus less saturated. Data science is therefore an extremely rich field and has many opportunities. Data science is highly requested, but low in data scientists' supplies.

3. A very well-paid career :

One of the highest paid jobs is data science. Glassdoor reports that the average annual rate for data scientists is $116,100. Data Science is therefore a very lucrative career opportunity.

4. Versatile data science :

Data science is used in numerous applications. It is widely used in the fields of healthcare, banking, consultancy and e-commerce. Data science is a multi-faceted field. You will therefore have the chance to work in different areas.

5. Science of Data improves data :

Companies are demanding that qualified data researchers process and analyse their data. They analyse and improve not only data but also quality. Data Science is therefore involved in enriching data and improving it for its company.

6. Highly renowned data scientists :

Data scientists make smarter business decisions for companies. Firms rely on data scientists and use their expertise to give their customers better results. Data scientists are therefore given an important role in the company.

7. No Boring Works More :

Data Science contributed to the automation of redundant activities by different industries. Companies use historical data to train machines for repeated tasks. The arduous work of people before has been simplified.

8. The science of data makes smarter products :

Data science involves the use of machine learning, which has allowed industry to create better, more customised products.

For example, e-commerce website recommendations provide users with personalised insights based on historical shopping. Computers have now been able to understand human behaviour and take decision-making based on data.

9. Save Lives Data Science :

Data science has improved significantly in the healthcare sector. Early-stage tumours are easier to detect with the development of machine learning. Many other health industries also use data science to assist their customers.

10. Data Science Can Build You Better :

Data Science not only offers you a great career, but also helps you to grow yourself. You can have an attitude that solves problems. Since many data science roles are a bridge between IT and management, you can enjoy the best of both worlds.

Roles and Responsibilities :

    Data scientists work in close collaboration with business players to understand their objectives and to identify the use of data to achieve these objectives. They develop processes for data modelling, create algorithms and predictive models to collect data from business requirements, analyse and share data with others. The process for data collection and analysis, while each project is different, generally follows the following path:

  • Ask the right questions to start the process of discovery
  • Data collection
  • Clean and process data
  • Data integration and storage
  • Initial data research and data analysis exploratory
  • Choose one or more possible algorithms and models
  • Apply techniques of data science, such as machine education, statistical modelling and artificial intelligence
  • Measuring and enhancing results
  • Present the stakeholders' final results
  • Make feedback-based adjustments
  • Repeat a new problem solving process.

Payscale :

The average salary for data scientists is 698K Dollar. An enterprise scientist with less than a year's experience can earn around 500K per year. Early data scientists with 1 to 4 years of experience have a yearly experience of 610K. A data scientist with a mid-level experience of 5 to 9 years earns 100K dollars per year in India. As your experience and skills increase, as senior data scientists in India, your earnings increase dramatically by more than 170K a year! Data Engineers are about Rs. 7 LPA in their early careers (1-4 years of experience). The wages of a data engineer are Rs. 121K as they move to the mid level (with five to nine years of experience). More than Rs.157K LPA can be made by data engineers with 15 years of work experience. And you can earn an average total compensation of Rs 900K when you are a mature and experienced data analyst, who has been in the sector or 10 to 19 years.

Show More

Key Features

ACTE Kolkata 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 Kolkata
Module 1: Introduction to Data Science with R
  • What is Data Science, significance of Data Science in today’s digitally-driven world, applications of Data Science, lifecycle of Data Science, components of the Data Science lifecycle, introduction to big data and Hadoop, introduction to Machine Learning and Deep Learning, introduction to R programming and R Studio.
  • Hands-on Exercise - Installation of R Studio, implementing simple mathematical operations and logic using R operators, loops, if statements and switch cases.
Module 2: Data Exploration
  • Introduction to data exploration, importing and exporting data to/from external sources, what is data exploratory analysis, data importing, dataframes, working with dataframes, accessing individual elements, vectors and factors, operators, in-built functions, conditional, looping statements and user-defined functions, matrix, list and array.
  • Hands-on Exercise -Accessing individual elements of customer churn data, modifying and extracting the results from the dataset using user-defined functions in R.
Module 3: Data Manipulation
  • Need for Data Manipulation, Introduction to dplyr package, Selecting one or more columns with select() function, Filtering out records on the basis of a condition with filter() function, Adding new columns with the mutate() function, Sampling & Counting with sample_n(), sample_frac() & count() functions, Getting summarized results with the summarise() function, Combining different functions with the pipe operator, Implementing sql like operations with sqldf.
  • Hands-on Exercise -Implementing dplyr to perform various operations for abstracting over how data is manipulated and stored.
Module 4: Data Visualization
  • Introduction to visualization, Different types of graphs, Introduction to grammar of graphics & ggplot2 package, Understanding categorical distribution with geom_bar() function, understanding numerical distribution with geom_hist() function, building frequency polygons with geom_freqpoly(), making a scatter-plot with geom_pont() function, multivariate analysis with geom_boxplot, univariate Analysis with Bar-plot, histogram and Density Plot, multivariate distribution, Bar-plots for categorical variables using geom_bar(), adding themes with the theme() layer, visualization with plotly package & building web applications with shinyR, frequency-plots with geom_freqpoly(), multivariate distribution with scatter-plots and smooth lines, continuous vs categorical with box-plots, subgrouping the plots, working with co-ordinates and themes to make the graphs more presentable, Intro to plotly & various plots, visualization with ggvis package, geographic visualization with ggmap(), building web applications with shinyR.
  • Hands-on Exercise -Creating data visualization to understand the customer churn ratio using charts using ggplot2, Plotly for importing and analyzing data into grids. You will visualize tenure, monthly charges, total charges and other individual columns by using the scatter plot.
Module 5: Introduction to Statistics
  • Why do we need Statistics?, Categories of Statistics, Statistical Terminologies,Types of Data, Measures of Central Tendency, Measures of Spread, Correlation & Covariance,Standardization & Normalization,Probability & Types of Probability, Hypothesis Testing, Chi-Square testing, ANOVA, normal distribution, binary distribution.
  • Hands-on Exercise -– Building a statistical analysis model that uses quantifications, representations, experimental data for gathering, reviewing, analyzing and drawing conclusions from data.
Module 6: Machine Learning
  • Introduction to Machine Learning, introduction to Linear Regression, predictive modeling with Linear Regression, simple Linear and multiple Linear Regression, concepts and formulas, assumptions and residual diagnostics in Linear Regression, building simple linear model, predicting results and finding p-value, introduction to logistic regression, comparing linear regression and logistics regression, bivariate & multi-variate logistic regression, confusion matrix & accuracy of model, threshold evaluation with ROCR, Linear Regression concepts and detailed formulas, various assumptions of Linear Regression,residuals, qqnorm(), qqline(), understanding the fit of the model, building simple linear model, predicting results and finding p-value, understanding the summary results with Null Hypothesis, p-value & F-statistic, building linear models with multiple independent variables.
  • Hands-on Exercise -Modeling the relationship within the data using linear predictor functions. Implementing Linear & Logistics Regression in R by building model with ‘tenure’ as dependent variable and multiple independent variables.
Module 7: Logistic Regression
  • Introduction to Logistic Regression, Logistic Regression Concepts, Linear vs Logistic regression, math behind Logistic Regression, detailed formulas, logit function and odds, Bi-variate logistic Regression, Poisson Regression, building simple “binomial” model and predicting result, confusion matrix and Accuracy, true positive rate, false positive rate, and confusion matrix for evaluating built model, threshold evaluation with ROCR, finding the right threshold by building the ROC plot, cross validation & multivariate logistic regression, building logistic models with multiple independent variables, real-life applications of Logistic Regression
  • Hands-on Exercise -Implementing predictive analytics by describing the data and explaining the relationship between one dependent binary variable and one or more binary variables. You will use glm() to build a model and use ‘Churn’ as the dependent variable.
Module 8: Decision Trees & Random Forest
  • What is classification and different classification techniques, introduction to Decision Tree, algorithm for decision tree induction, building a decision tree in R, creating a perfect Decision Tree, Confusion Matrix, Regression trees vs Classification trees, introduction to ensemble of trees and bagging, Random Forest concept, implementing Random Forest in R, what is Naive Bayes, Computing Probabilities, Impurity Function – Entropy, understand the concept of information gain for right split of node, Impurity Function – Information gain, understand the concept of Gini index for right split of node, Impurity Function – Gini index, understand the concept of Entropy for right split of node, overfitting & pruning, pre-pruning, post-pruning, cost-complexity pruning, pruning decision tree and predicting values, find the right no of trees and evaluate performance metrics.
  • Hands-on Exercise -Implementing Random Forest for both regression and classification problems. You will build a tree, prune it by using ‘churn’ as the dependent variable and build a Random Forest with the right number of trees, using ROCR for performance metrics.
Module 9: Unsupervised learning
  • What is Clustering & it’s Use Cases, what is K-means Clustering, what is Canopy Clustering, what is Hierarchical Clustering, introduction to Unsupervised Learning, feature extraction & clustering algorithms, k-means clustering algorithm, Theoretical aspects of k-means, and k-means process flow, K-means in R, implementing K-means on the data-set and finding the right no. of clusters using Scree-plot, hierarchical clustering & Dendogram, understand Hierarchical clustering, implement it in R and have a look at Dendograms, Principal Component Analysis, explanation of Principal Component Analysis in detail, PCA in R, implementing PCA in R.
  • Hands-on Exercise -Deploying unsupervised learning with R to achieve clustering and dimensionality reduction, K-means clustering for visualizing and interpreting results for the customer churn data.
Module 10: Association Rule Mining & Recommendation Engine
  • Introduction to association rule Mining & Market Basket Analysis, measures of Association Rule Mining: Support, Confidence, Lift, Apriori algorithm & implementing it in R, Introduction to Recommendation Engine, user-based collaborative filtering & Item-Based Collaborative Filtering, implementing Recommendation Engine in R, user-Based and item-Based, Recommendation Use-cases.
  • Hands-on Exercise -Deploying association analysis as a rule-based machine learning method, identifying strong rules discovered in databases with measures based on interesting discoveries.
Module 11: Introduction to Artificial Intelligence (self paced)
  • introducing Artificial Intelligence and Deep Learning, what is an Artificial Neural Network, TensorFlow – computational framework for building AI models, fundamentals of building ANN using TensorFlow, working with TensorFlow in R.
Module 12: Time Series Analysis (self paced)
  • What is Time Series, techniques and applications, components of Time Series, moving average, smoothing techniques, exponential smoothing, univariate time series models, multivariate time series analysis, Arima model, Time Series in R, sentiment analysis in R (Twitter sentiment analysis), text analysis.
  • Hands-on Exercise -Analyzing time series data, sequence of measurements that follow a non-random order to identify the nature of phenomenon and to forecast the future values in the series.
Module 13: Support Vector Machine - (SVM) (self paced)
  • Introduction to Support Vector Machine (SVM), Data classification using SVM, SVM Algorithms using Separable and Inseparable cases, Linear SVM for identifying margin hyperplane.
Module 14: Naïve Bayes (self paced)
  • what is Bayes theorem, What is Naïve Bayes Classifier, Classification Workflow, How Naive Bayes classifier works, Classifier building in Scikit-learn, building a probabilistic classification model using Naïve Bayes, Zero Probability Problem.
Module 15: Text Mining (self paced)
  • Introduction to concepts of Text Mining, Text Mining use cases, understanding and manipulating text with ‘tm’ & ‘stringR’, Text Mining Algorithms, Quantification of Text, Term Frequency-Inverse Document Frequency (TF-IDF), After TF-IDF.
Module 16: Case Study
  • This case study is associated with the modeling technique of Market Basket Analysis where you will learn about loading of data, various techniques for plotting the items and running the algorithms. It includes finding out what are the items that go hand in hand and hence can be clubbed together. This is used for various real world scenarios like a supermarket shopping cart and so on.
Show More
Show Less
Need customized curriculum?

Hands-on Real Time Data Science Projects

Project 1
Uber Data Analysis in R Project

Uber Data Analysis through Visualisations in R. Data storytelling is an important component of Machine Learning through which companies are able to understand.

Project 2
Driver Drowsiness Detection in Python Project

The objective of this intermediate Python project is to build a drowsiness detection system that will detect that a person's eyes are closed for a few seconds.

Project 3
Chatbot Project in Python

In this Python project with source code, we are going to build a chatbot using deep learning techniques and trained on the dataset which contains categories, pattern and responses.

Project 4
Handwritten Digit Recognition Project

The aim of this project is to implement a classification algorithm to recognize handwritten digits and pattern recognition that no single classifier performs the best.

Our Best Hiring Placement Partners

ACTE Kolkata  offers arrangement openings as extra to each understudy/proficient who finished our study hall or internet preparing. A portion of our understudies are working in these organizations recorded underneath. We offers arrangement backing is probably the best assistance upon fruitful finish of any course from our institute we help the trained to land their fantasy position by giving placement opportunities.
  • We will schedule interview calls for applicants and prepare them for face-to-face contact after they have completed 70% of the Data Science training course material.
  • Work plan for the right contenders. absolutely an undertaking coordinated course, which covers the specific progress starting from the extraordinarily pressing and walk around the basic level and, thusly, it gives tremendous level of data in singular new development.
  • During the social gathering, implying this master accomplishment assertion on student continue has a huge impact and makes the constancy of understudy likewise improves it's anything but's a more broad level of work openings.
  • Our circumstance get groups together with over 600+ accomplices. Our outline specialists work with the total of our helpful understudies and firms like as HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM, HDFC, AMAZON, PAYPAL, and others from one side.
  • We have separate applicants entryways for circumstance, here understudy will get all the get-together schedules and we brief understudy through messages.
  • We will make plans to conduct Mock Exams and Mock Interviews to find the skillful Candidate for our hiring partners.

Get Certified By MCSE: Data Management and Analytics & Industry Recognized ACTE Certificate

Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees. Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.

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

About Satisfactory Data Science Trainer

  • Our Data Science Training in Kolkata. Our mentor give a blend of class, instructor drove on the web, and E-learning decisions to ensure that competitors get changed training and advance their assumption to learn and change.
  • Our Data Science Training mentor are incredibly outfitted specialists with more than 9+ wide stretches of unsurprising position who are comprehensively seen as the best in the business and now serve for tremendous affiliations.
  • Our mentor give a blend of class, instructor drove on the web, and E-learning decisions to ensure that competitors get changed training and advance their assumption to learn and change.
  • Our trainers are industry-experts and subject specialists who have mastered on running applications providing Best Data Science Training to the applicants.
  • Trainers are also help candidates to get placed in their respective company by Employee Referral / Internal Hiring process.
  • Latest interpretation Data Science Training accounts guaranteed and Complete plan of stories like live online social events.

Data Science Course Reviews

Our ACTE Kolkata Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.



ACTE is the best training institute for Data science and Data Analytics in BTM Layout. The trainers are well experienced and the methodology of teaching is top notch. They provide practicals along with theoretical sessions for complete understanding of the concepts. They even provide placement assistance after course completion as well.


Software Engineer

An excellent Data Science authorized training center at Kolkata. Good facilites and effective trainers in ACTE. Prompt and transparent placement process. They also provide effective counselling through sessions every month to guide candidates....


Best DATA SCIENCE training institute in Tambaram with Realtime client projects and dedicated support team. I have taken Data science training on this January and completely happy with their teachings, projects and job support after the course completion. It's a One stop destination for your data science And AI training in BTM Layout.



ACTE for your career switch to Data Science..They have well experienced Trainers in ACTE who can make you industry ready. Curriculum is quite unique and includes current industry needs. They give very good job assistance also.


Software Engineer

Its a good institute for Data Science in Porur. The teaching staff is good, they give us day wise assignments which helped me to hands on algorithms of machine learning and also provide us the backup classes. The access they provide is very helpful to listen the classes repeatedly. They provide good placement assistance. Thanks social ACTE team for your support and guidance.

View More Reviews
Show Less

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
    • Gives
    • 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
Show More
Request for Class Room & Online Training Quotation

      Related Category Courses

      data science with sas training acte
      Data Science With SAS Training in Chennai

      Beginner & Advanced level Classes. Hands-On Learning in Data Science Read more

      data science with r training acte
      Data Science with R Training in Chennai

      Beginner & Advanced level Classes. Hands-On Learning in Data Science Read more

      data science with python training acte
      Data Science With Python Training in Chennai

      Live Instructor LED Online Training Learn from Certified Experts Beginner Read more

      python training acte
      Python Training in Chennai

      Live Instructor LED Online Training Learn from Certified Experts Beginner Read more

      r programing training acte
      R Programming Training in Chennai

      Beginner & Advanced level Classes. Hands-On Learning in R Programming. Read more

      machine Learning training acte
      Machine Learning Training in Chennai

      Live Instructor LED Online Training Learn from Certified Experts Beginner Read more

      ai training acte
      Artificial Intelligence Course in Chennai

      Live Instructor LED Online Training Learn from Certified Experts Advanced Read more