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Data Science Training in Pune

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  • Get Best Training on Novice to Advanced level Classes.
  • Practical Classes for both beginners and experience
  • Precedent level Training sessions on Data Science Tools.
  • Endurance access for Student’s Portal, Study Materials, Videos & Top MNC Interview Question.
  • Best Approaches on Trending Data Science Concepts with Nominal Cost.
  • Delivered by 9+ years of Data Science Certified Expert | 12402+ Students Trained & 350+ Recruiting Clients.
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Upcoming Batches

05- Dec - 2022

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

07- Dec - 2022

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

03- Dec - 2022

Weekend Regular

(10:00 AM - 01:30 PM)

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

03- Dec - 2022

Weekend Fasttrack

(09:00 AM - 02:00 PM)

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Awaken Your Career Possibilities with Our Data Science Experts

  • ACTE Data Science online training provides Fresher Candidates with Placement Assistance and Professional References.
  • ACTE has designed a comprehensive training course which meets all the job requirements.
  • Our Professionals helps on project summaries for real-time.
  • IBM Data Science Professional Certificate Guidance Support for Exam Dumps Sophisticated Lab Facility and Training Tutors.
  • We act as a company partner for the recruitment of companies.
  • Our Placement team the qualified, productive candidates from the day one to the industry.
  • ACTE helps applicants to prepare for their interviews by organising Mock interviews.
  • Learning 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
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This is How ACTE Students Prepare for Better Jobs


Course Objectives

  • Because big companies don't often appreciate freshers for these jobs, experience with real-time data science initiatives will be a plus.
  • Our Data Science course focuses on covering the essential curricula as well as real-world business challenges.
  • Our real projects will help you gain a thorough understanding of the subject and prepare you for interviews with leading organizations for Data science positions.
  • Our instructors can share their knowledge and assist you in resolving period problems.
  • To begin a career in Data Science, you must complete either online or classroom training.
You'll require knowledge of a variety of programming languages, including Python, Perl, C/C++, SQL, and Java, with Python being the most commonly used dedication to writing language in Data science employment. These programming languages make it easier for data scientists to manage large amounts of unstructured data.
  • The curriculum is usually designed by the most recent industry standards. Our instructors provide real-time instruction with live projects to help you gain a better knowledge of the subject.
  • We provide training in a variety of formats, including online, in a classroom, and weekend batches.
  • Our training plan is extremely adaptable to your on-the-market requirements.
  • Because our experts can guide you through the process by sharing their real-time experiences in relevant sectors, our Data science course can help you crack related interviews at top MNCs.
  • Expertise, Data Science knowledge, and appropriate tools and technology are all required for the Data Science position.
  • IT Professionals
  • Banking and Finance Professionals
  • Marketing Managers
  • Analytics Managers
With the advent of technology, Data Science has a wide range of applications in India. Data science has risen to the top of the most popular professional paths. Having an engineering or elated stream as a bachelor's degree. Should be able to operate Python, Pig, Hadoop, SQL, and other programming languages and software systems.
The course has been developed to help applicants get a head start in the areas of information science and machine learning. Students who completed the course have gone on to work as Data Scientists, Machine Learning Engineers, Data Analysts, Analytics Experts, and other positions at prominent analytics firms.
  • Learn the fundamentals of many applied mathematics concepts.
  • Understand and apply hypothesis testing methodologies to help you make better business decisions.
  • Understand and use information analysis techniques such as linear and non-linear regression models, as well as classification approaches.
  • This necessitates a grasp of how money and information move in a business, as well as the ability to apply that knowledge to identify business prospects.

How much time does it take to become a data scientist?

Your professional ambitions, as well as the amount of money and time you are prepared to invest in your education, will decide how long it takes you to become a data scientist. There are four-year bachelor's degrees and three-month boot camps available in data science. If you already have a bachelor's degree or have finished a Bootcamp, you might wish to pursue a master's degree, which may be done in as short as a year. The majority of data scientists, according to the Burtch Works research, hold a doctorate.

Is it worthwhile to pursue a career in data science certification Course?

Data science is one of the top professional alternatives in the twenty-first century for a variety of reasons. For many people, the need and breadth of this technology are the key motivators for pursuing a career in this field. Furthermore, the pay scale given in this field is piquing young people's interest in working as Data Scientists. The employment options offered in this area are often regarded as some of the best-paying in the country. Many present employment roles are projected to be replaced as data science continues to spread its effect across many disciplines. As a result, data science is the greatest option for anyone seeking a long-term job.

What are the preconditions to learning Data Science Course in Pune?

  • Python is a computer language that may be used to create programs. Python is the most popular coding language I encounter in data science professions, along with Java, Perl, and C/C++.
  • Hadoop distribution platform.
  • Database and coding in SQL.
  • Apache Spark is abbreviated as Spark.
  • AI and machine learning are two terms that are used interchangeably.
  • Data visualization.
  • Unstructured data is data that hasn't been organized.

what are the various job role available in the data science field?

This field has a lot of interesting work prospects. Many young individuals desire to work in these fields in the future. Let's take a look at some of the most important Data Science job openings.
  • Data Analyst.
  • Statistician Business.
  • Analyst Database.
  • Administrator.
  • Data Engineer.
  • Data Scientist.

What is the pay scale in the field of data science?

One of the highest-paying employment titles in the country is said to be in the Data Science sector. In India, a data scientist's yearly income is projected to be Rs. 8.2 lakh. The compensation ranges from 6 to 20 lakh rupees per year. In India, there are roughly 40, 000+ job openings in the sector of Data Science for various professional roles. Great Learning offers India's top data science course, which includes job placement.
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Overview of Data science Training in Pune

Data science is a mix of different tools, algorithms and concepts of machine learning to detect hidden patterns from the raw data. A data scientist examines the data from a variety of viewpoints, often not previously recognised. Data science is therefore mostly used to create judgments and forecasts using predictive causal analytics, predictive analysis and machine learning. By its successes in the software training area and the company's reputation for providing corporative training to its workers ACTE has acquired the status of the finest Data science Course in Pune. It has over 15+ years of software training expertise and has trained and placed more than 20,000 students with outstanding wage packages in all the leading MNCs.


Additional Info

Why learn Data Science?

The data we had traditionally were largely organised and modest in size and could be examined by simple BI instruments. Contrary to the mainly organised data in conventional systems, the majority of the data nowadays is unstructured or semi-structured. Let's look at the below data trends that suggest that more than 80% of the data will be unstructured.

  • This data comes from several sources, including financial records, text files, multifunctional forms, sensors and tools. This enormous amount and variety of data cannot be processed by simple BI tools. For this reason, we need increasingly complicated analytical tools and algorithms for processing, analysis and the development of relevant insights. Not simply because of the popularity of data science.
  • Let's take a closer look at how data science is applied in different fields. How can you comprehend your clients' specific requirements using current data such as customer history of navigation, acquisition histories, age and revenue? You had all this without any uncertaintyLet's explore how predictive analytics can leverage data science.
  • Take for example weather predictions. Data may be collected and evaluated from ships, planes, radar, satellites to construct models. These models not only anticipate the weather but also assist prevent natural disasters. It will help you take the right action in advance and save many valuable lives.

The main of Data Science Lifecycle:

Here is a quick summary of the major phases in the life cycle of data science:

Discovery:- It is essential to grasp the different specifications, needs, priorities and budgets necessary before beginning the project. You need to be able to ask the correct questions. Here, you evaluate if you have the resources necessary to support the project, including people, technology, time and data. At this stage the business challenge has to be framed and initial hypotheses (IH) formulated to be tested.

Processing of data:- In this phase, you need an analytical sandbox in which you may analyse the whole project. Before modelling, you need to examine, pre-process and condition data. In order to obtain your data in the sandbox, you will also execute ETLT (extract, transform, load and transform). Let's look at the following flow of statistical analysis. You may use R to purify, process and view data. This helps you to identify the outliers of the variables and to create a connection. It is time to perform exploration analysis once you have cleaned and prepped the data. Let's see how it is possible.

Model Planning: Model Data Science:- The strategies and approaches for drawing links between variables are defined. These connections provide the basis for the algorithms that you are using in the following stage. You use numerous statistical formulae and visualisation tools to implement Exploratory Data Analytics (EDA).

Model construction:- You will generate data sets for training purposes and testing reasons in this phase. Here is if your present tools are sufficient to run the models or a more robust environment is needed (like fast and parallel processing). To create the model, you will study several learning approaches such as grading, association and grouping.

Operationalizing:- Furthermore, a pilot project is occasionally executed in a production environment in real-time. This gives you a good view before complete deployment of your performance and other associated restrictions on a small scale.

Transmit results:- Now it is vital to assess if you have achieved your aim in the first phase. So in the last stage, all of the important findings are identified, the stakeholders are communicated and whether the project outcomes are successful or a failure based on the criteria.

What skills will you acquire from our Data Science Training?

Training in data science helps you become an expert in data sciences. It will improve your abilities by helping you comprehend and evaluate actual data phenomena and offer the practical experience needed to solve projects based on the industry in real-time.

  • You will be educated by our professional professors throughout this data science course.
  • Learn more about a data scientist's roles.
  • Analyze several data types with R.
  • Describe the life cycle of data science.
  • Work with many formats such as XML, CSV, and so on.
  • Learn Data Transformation tools and approaches.
  • Exchange methods for data mining and tand its application.
  • Analyze information with R machine learning algorithms.
  • Explain time series and the principles involved.
  • Conduct text mining and sentimental text data analysis.
  • Learn about visualisation and optimisation of data.

Job roles and responsibilities of Datascience:

In various scientific areas, data scientists are individuals who are cracking difficult data issues. They work with various components in mathematics, statistics, informatics, etc (though they may not be an expert in all these fields). They employ state-of-the-art technology to identify answers and to draw conclusions which are important to the growth and development of an organisation. In comparison with the raw data available from structured and unstructured formats, data scientists provide the data in a far more usable way.

  • After contemplating that a data scientist pulls a great deal of knowledge from science areas and applications, whether it be statistics or mathematics, the name "data scientist' was coined.
  • This is nothing but the unattended model because you have no specified group labels. Clustering is the most frequent approach used to find patterns.
  • Let's just suppose you work at a telephone business and you have to build a network in an area, installing towers.
  • As may be seen in the following picture, the data analysis involves to some extent descriptive analysis and prediction.
  • Preserve the integrity and organization of the code continuously.
  • Optimize web apps in laptops, desktops, tablets, and smarts to boost cross-platform interoperability.
  • Troubleshoot issues and problem-solving in one of the three levels.
  • They employ state-of-the-art technology to identify answers and to draw conclusions which are important to the growth and development of an organisation.
  • In this section, BI allows you to capture, prepare and query data from internal and external sources and to construct dashboards that answer questions such as a quarterly revenue analysis or business issues.

The top 10 technological developments of Data science:

Data and analytical managers should concentrate on in order to invest in preparation for the reset.

Smarter, quicker, accountable AI:- The present pandemic situation includes the provision of essential insights and predictions about the spread of the virus and the effect and efficiency of interactions via IA methods, such as machine learning (ML), optimisation and natural language processing (NLP). Critical realignment of the supply chain and n is AI and machine learningAI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems can model and stimulate complex systems particularly now when pre-COVID models based on historical data may no longer be valid.

Decline of the dashboard:- Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration. As a result, the amount of time users spend using predefined dashboards will decline. The shift to in-context data stories means that the most relevant insights will stream to each user based on their context, role or use. These dynamic insights leverage technologies such as augmented analytics, NLP, streaming anomaly detection and collaboration.

Decision intelligence:- Decision intelligence brings together a number of disciplines, including decision management and decision support. It encompasses applications in the field of complex adaptive systems that bring together multiple traditional and advanced disciplines. It provides a framework to help data and analytics leaders design, compose, model, align, execute, monitor and tune decision models and processes in the context of business outcomes and behavior.

X analytics:- Gartner coined the term “X analytics” to be an umbrella term, where X is the data variable for a range of different structured and unstructured content such as text analytics, video analytics, audio analytics, etc. Data and analytics leaders use X analytics to solve society’s toughest challenges, including climate change, disease prevention and wildlife protection.

Augmented data management:- Augmented data management uses ML and AI techniques to optimize and improve operations. It also converts metadata from being used in auditing, lineage and reporting to powering dynamic systems. Augmented data management products can examine large samples of operational data, including actual queries, performance data and schemas. Using the existing usage and workload data, an augmented engine can tune operations and optimize configuration, security and performance.

Cloud is a given:- As data and analytics moves to the cloud, data and analytics leaders still struggle to align the right services to the right use cases, which leads to unnecessary increased governance and integration overhead. The question for data and analytics is moving from how much a given service costs to how it can meet the workload’s performance requirements beyond the list price.

Data and analytics worlds collide:- Data and analytics capabilities have traditionally been considered distinct capabilities and managed accordingly. Vendors offering end-to-end workflows enabled by augmented analytics blur the distinction between once separate markets. The collision of data and analytics will increase interaction and collaboration between historically separate data and analytics roles. This impacts not only the technologies and capabilities provided, but also the people and processes that support and use them.

Advantages of Data Science:

The various benefits of Data Science are as follows:

  • It’s in Demand:- Data Science is greatly in demand. Prospective job seekers have numerous opportunities. It is the fastest-growing job on Linkedin and is predicted to create 11.5 million jobs. This makes Data Science a highly employable job sector.

  • The abundance of Positions:- There are very few people who have the required skill-set to become a complete Data Scientist. This makes Data Science less saturated as compared with other IT sectors. Therefore, Data Science is a vastly abundant field and has a lot of opportunities. The field of Data Science is high in demand but low in supply of Data Scientists.

  • A Highly Paid Career:- Data Science is one of the most highly paid jobs. According to Glassdoor, Data scientists make an average of 1,16,100 per year. This makes Data Science a highly lucrative career option.

  • Data Science is Versatile:- There are numerous applications of Data Science. It is widely used in health-care, banking, consultancy services, and e-commerce industries. Data Science is a very versatile field. Therefore, you will have the opportunity to work in various fields.

  • Data Science Makes Data Better:- Companies require skilled Data Scientists to process and analyze their data. They not only analyze the data but also improve its quality. Therefore, Data Science deals with enriching data and making it better for their company.

  • Data Scientists are Highly Prestigious:- Data Scientists allow companies to make smarter business decisions. Companies rely on Data Scientists and use their expertise to provide better results to their clients. This gives Data Scientists an important position in the company.

  • No More Boring Tasks:- Data Science has helped various industries to automate redundant tasks. Companies are using historical data to train machines in order to perform repetitive tasks. This has simplified the arduous jobs undertaken by humans before.

  • Data Science Makes Products Smarter:- Data Science involves the usage of Machine Learning which has enabled industries to create better products tailored specifically for customer experiences. For example, Recommendation Systems used by e-commerce websites provide personalized insights to users based on their historical purchases. This has enabled computers to understand human-behavior and take data-driven decisions.

  • Data Science can Save Lives:- The Healthcare sector has been greatly improved because of Data Science. With the advent of machine learning, it has been made easier to detect early-stage tumors. Also, many other health-care industries are using Data Science to help their clients.

  • Data Science Can Make You A Better Person:- Data Science will not only give you a great career but will also help you in personal growth. You will be able to have a problem-solving attitude. Since many Data Science roles bridge IT and Management, you will be able to enjoy the best of both worlds.

The Various Career opportunities of Data Science:

1. Data Scientist:- The data scientist works in several fields. In accordance with the business objectives, the data scientist might define the problem description, project objectives. They use artificial intelligence, machine learning to discover models and trends and create predictions based on data. They need a solid foundation in artificial intelligence, machine learning, statistics, and data engineering.

2. Data Analyst:- The data analyst often works together with the company and management to identify project goals and business needs. It enables appropriate data to be collected and data to be explored. You convert data into patterns and trends and analyze them. The models are also presented and the data are shown in order for the team to convert the designs into operative products. It requires outstanding interpersonal skills with technical abilities like programming, databases, data analysis, and tools for data visualization. Machine learning skills and an in-depth grasp of cloud platforms like Azure, IBM, and Google are the main goals.

3. Data Engineer:- Traditionally, organizations hire and manage data every day by database administrators. They are responsible for the preservation of the integrity and performance of the databases of the business and for guaranteeing data security. They must be knowledgeable with classic relation databases, retrieval of disasters and backup methods, as well as reporting tools.

4. Enterprise Data Architect:- Data architects and data managers provide enterprise data management services at the strategic level, guaranteeing the quality, accessibility, and security of data. The company data architects establish strategic plans for data management, pipelines, and repositories. They construct and manage the database of an organization by defining technological layers, performance needs, and database sizes. In addition, they collaborate with data engineers and managers to guarantee the strategic usage of the performance, data protection, and security of the data.

Pay scale in Data science:

According to Glassdoor data, data scientists can expect to make an average of 117,345 per year. But that number can vary based on where a data scientist works, or their years of experience. For example, a data scientist working at a company with up to 500 employees can expect to earn 112,365 per year, while a data scientist with 15-plus years of experience can earn an average of 141,921 a year, Glassdoor data shows.

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Key Features

ACTE Pune offers Data Science Training in more than 27+ branches with expert trainers. Here are the key features,
  • Get Qualified from Professional Expert
  • 100% Job placements
  • Industry Expert Faculties
  • Learn Data science from scratch
  • 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.


Synopsis of Data Science Course in Pune
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.
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Get Hands-on Knowledge with Industrial Live Data Science Projects

Project 1
Recognition of Speech and Emotion

In this project, we are using Librosa to perform Speech and Emotion Recognition to identify the emotion and speech from a combination of tone and pitch of human voice.

Project 2
Driver Drowsiness Detection System

This project will help to recognize whenever the driver may get drowsy & fall asleep while driving by creating a model to detect the sleepy driver and raises an alert alarm to indicate.

Project 3
Customer Segmentations Project

The project uses the K-means clustering algorithm to perform the visualizations and distribute like gender specification to find the customers annual value and scores.

Project 4
Gender and Age Detection

It is an ML Project based on computer visioning, and through this Data Science project, you get familiar with a practical application of convolutional neural networks (CNN).

Our Best Placement Partners

ACTE Pune offers placement opportunities is meant to provide applicants with hands-on Data Science training in the classroom or online to assist them gain industry exposure in understanding Data Science platforms, techniques, and applications in order to construct and execute effective Coding campaigns
  • For our applicants, a program is created that includes mock placements and mock interviews.
  • Customized training is provided to our candidates in order to clear their doubts related to any topic taught tot them.
  • Learners go through a thorough placement process to ensure that they acquire the positions they want.
  • Our applicants will be placed in companies such as TCS, Infosys, Microsoft, and many others.
  • After completing their training and mocks, the candidates are awarded a Data Science certificate.
  • Students are also provided a notification reminder so that they do not miss their mocks.

Get Accredited in Data Science with Industry Recognized ACTE Certificate

ACTE Data Science Training Certificate authorized by all Worldwide Organizations and all over the globe. After completion of the entire program will provide the certificates for both the candidates and the professional instructors. Our trainers helped the candidates to get certified the other certification like CCA and CCP are the top-level proving your advanced skills and deep knowledge of Machine Learning. ACTE Certification in Data Science Training will enhance the significance of your resume. It will lead you to a wide range of opportunities in your Career Path. This Certificate will help you to adopt new skills in the development of advanced concepts of Data Science.

Our ACTE Instructors will help the students to grab the knowledge on Other Data Science Programming and trained them to get other certification which is listed below:
  • Dell EMC Proven Professional Certification Program
  • Certified Analytics Professional
  • SAS Academy for Data Science
  • Microsoft Certified Solutions Expert
  • Cloudera Certified Associate
  • Cloudera Certified Professional - CCP Data Engineer
  • Data Science Certificate
  • Amazon AWS Big Data Certification
  • Oracle Certified Business Intelligence
  • Knowing a few algorithms well is better than knowing about many algorithms and linear regression, k-means clustering, and logistic regression well, can explain and interpret their results.
  • Most of the time, once you use associate degree formula, it'll be a version from a library. You’ll rarely be implementations SVM concepts.
  • Adopt a resource from good study books and e-learning methods according to your exam preparation.
  • Join Our ACTE Data Science Training Course get communicate with our instructors will get an idea regarding the subject and schedule the study plan for the certification exam.
With Data Science Training certificate you will hire for the following jobs:
  • Data Analyst
  • Data Engineers
  • Database Administrator
  • Machine Learning Engineer
  • Data Scientist
  • Data Architect
  • Statistician
  • Business Analyst
  • Data and Analytics Manager

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

Our Skillful Data Science Trainers

  • Our Data Science trainers have experience of more than 9+ years in their respective industries.
    • Our Instructor deliver and help our applicants for making and creating real-time project summaries.
    • Mock placement procedures are organized by our trainers for our prospects so our Learners have an idea how actual interviews are taken.
    • Our Data Science instructors are highly qualified and create a comprehensive course to ensure our candidates' success.
    • Because our instructors teach our applicants from the ground up, the principles are crystal apparent in Data Science.
    • Our Trainers also assist our candidates in developing a good resume in order for them to land their desired jobs.

Data Science Course Reviews

Our ACTE Pune 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

I am really happy and I want to say something about ACTE, This is a very good place to learn Data Science. And the trainer helped me to understand about Data Science. I hope this is the correct place to learn IT course. I suggest if anyone wants to learn course, I recommend ACTE Institute in Pune.


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.

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Data Science Course FAQs

Looking for better Discount Price?

Call now: +9193833 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 ScienceCourse 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 93833 99991 / 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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