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Data Science Training in India

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20- Mar - 2023

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22- Mar - 2023

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

25- Mar - 2023

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25- Mar - 2023

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Maintain the project role and play a role in the IT company.

  • In this course, students learn machine learning, statistical analysis, and how to work with data from different sources.
  • In the next section, we are going to discuss the roles and skills that are required for data science. Additionally, you'll learn what it takes to customize your data and how to adapt it to different audiences.
  • There will also be a discussion of how to analyze data effectively. Data science projects are executed through various approaches for planning, executing, and presenting. The tools and techniques on this page will help you get started in data science and maximize your data's potential.
  • From this course, you will acquire a very comprehensive understanding of data science. In this lecture, we'll explore a variety of fields in this field, including Data Scientist, Data Engineer, and Product Analyst.
  • In this course, you will be exposed to tools such as R, Python, and the command line for gathering and analyzing data. A/B testing and market analysis will be discussed along with several other topics in the course.
  • Several major technology companies will be participating at the event this year, including Amazon, Square, Facebook, Microsoft, Google, and AirBnB.
  • You'll find explanations and solutions for all course questions, including your quizzes. In addition to becoming an invaluable tool to help you prepare for exams, the program also serves as a handy tool while you are working.
  • You might find it helpful to be familiar with the following topics during an interview.
  • This curriculum will give students the opportunity to gain a deeper understanding of the subject matter. We provide students with the opportunity to prepare for interviews or find employment at reputable companies after they completing our program.
  • 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.
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Course Objectives

Furthermore, providing basic training in data science will help you complete valuable certifications, undertake projects in real-time and help to take on positions in the leading companies in the industry. There are different options for taking this training - self-sustaining training, online instructor training, and corporate training based on your availability.
Data scientists are demanding more and more every day. There is enormous data on the market, but the challenge is to analyze this database that shows the business route for growth. Today, companies are struggling to leverage large-scale data analytics and data science to take advantage of the first mover first. Each organization realized that data scientists needed to benefit as much as possible from the data available.
Certify yourself for the following roles in the field of data science:
  • Professionals in big data, analysts, and business intelligence
  • Professional Machine Learning
  • Architects of predictive analysis and information
  • Statisticians of big data
  • People looking for a career in data science
The only thing you need for this training is your interest and willingness. We encourage you to pay in two installments even if the total amount cannot be paid at once, but don't stop you from registering. It focuses entirely on your learning, knowledge, and a good job.
The learners will be able to master the following areas after the completion of this training:
  • R integrates to the ecosystem of Hadoop
  • Linear regression and logistics
  • Segmentation of clustering, analysis, and prediction
  • Recommendation systems deployment
  • Interpretation of data, plotting, and sampling techniques
The average wage of a data scientist at the entry-level can be 508,682/- based upon the answers received from The average wage of 610 811/- is expected for IT professionals with 5-9 years' experience, while the data scientist can expect INR 17,24,618 with 10 to 19 years experience. A data scientist in the US can earn an average of 113,309 INR.
The name Data Scientist itself is a prestigious job, it has a great weight. You earn more comparatively compared to other jobs at the same level of experience and for the same kind of education. You're only concerned about it! This role is waiting for you if you wish to work intelligently and creatively and earn more.

What are the roles and responsibilities of a Data Scientist?

As a data scientist, you have sufficient capacity to give your business direction – the shortest way to succeed. You analyze your data, analyze data, use statistical tools to predict business performance solutions

Does Data Science require coding background?

You want to possess an understanding of various programming languages, like Python, Perl, C/C++, SQL, and Java, with Python being the foremost general cryptography language required in data science roles. These programming languages help data scientists to arrange unstructured data sets.

What are different milestones for a Data Scientist?

A data scientist aspirant's first milestone is to learn Python, R, and hands-on analysis instruments such as SAS. The next phase could be to learn about Big Data Analysis and statistical instruments, such as Hadoop, Spark. Another milestone could be the understanding of the large array of data, diagrams, maps, and reports.

What are the basic requirements for learning a Data Science training course?

Data science challenges the fundamentals of statistics and arithmetic, which should be clear to be able to analyze the issues that are at hand. To resolve business problems, you would like to possess soft skills like team management and control over the projects to fulfill the deadlines. You may find many data scientists with a bachelor's degree in statistics and machine learning but it's not a requirement to learn data science.

Why is it important to learn a Data Science training course?

Data scientists carefully use their skills in maths, statistics, programming, and alternative connected subjects to organize giant information sets... Data science is high in the order and explains however digital data is remodeling businesses and serving them to make chiseler and important selections. Therefore digital data is throughout for people that try to work as data scientists.
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Overview of Data Science Training in India

This Data Science Course in India is developed in such a manner that it meets the demands and expectations of persons of all educational backgrounds. The training is designed for both technical and technical background professionals. You will become an expert in Big Data Technologies, the world's most popular and fastest-growing field of expertise. Find jobs as Data Scientists, Data Analysts, Data Engineers, Data Developers, and more.


Additional Info

Why To Learn Data Science?

Data Science, with the amount of data being generated and the evolution of Analytics, has become increasingly important for most companies. From Finance, IT, Marketing, Retail, to Retail, and Retail, companies of all types use their data to their advantage. A Data Scientist is needed for all. Data Scientists are in great demand across the globe due to this phenomenon. In conclusion, a job as a software engineer in IBM is one of the best paying jobs for many people due to the kind of salary that the company offers. Data Scientists can come from any background and pursue a career in this field.

Components Of Data Science:

Data Science is comprised of 3 parts, namely:

Machine Learning:- Algorithms and mathematic models are used to teach machines how to adapt and learn from the world around them, which is the reason machine learning is called machine learning. Nowadays, time series forecasting is used in a great deal of trading, financial, and investment systems. In this approach, the machine uses historical data patterns to predict the outcome for the next few months or years. Machine learning has been applied here.

Big Data:- Human beings produce a vast amount of data every single day, including clicks, orders, videos, images, comments, articles, RSS Feeds, and more. It is commonly called Big Data, as these data are generally unstructured. Data from big data is converted from an unstructured state to a structured state using tools and techniques. Someone would like to keep track of the prices of products on e-commerce sites, for example. Through RSS feeds and Web APIs, he/she can access the same product data on multiple websites. Create a structured form of them.

Business Intelligence:- There is a lot of data produced each day by every company. By analyzing this data carefully and then presenting it in visual graph reports, good decisions can be made. After thoroughly examining the details and patterns the reports illustrate, the management can take the most effective decision.

Skills required to become a data scientist include:


An in-depth understanding of R:- This language is used for multiple purposes: data analysis, programming, statistical analysis, and data visualization

Python programming:- Since Python has rich libraries/packages for building and deploying models, it is most commonly used to implement mathematical models.

Microsoft Excel:- Data entry jobs generally require knowledge of Microsoft Excel. Formulas and equations, as well as diagrams, can be generated from very messy data in data analysis.

Hadoop Platform:- A distributed processing framework that is open source. A big data application uses it to manage processing and storage.

Coding/SQL database:- The main purpose of this tool is to prepare and extract datasets. You can also use it to analyze graphs and networks, search behavior, fraud detection, etc.

Technology:- Unstructured data readily available nowadays has to be accessed since there is so much of it. The process can be accomplished via APIs or through web servers.

Here Are The Top 5 Reasons To Become A Data Scientist.

1. Increasing demand:- By its high demand throughout the world, the job of Data Scientist has become a worldwide phenomenon. McKinsey & Company estimates that by 2018, there will be between 140,000 and 180,000 fewer data scientists in the U.S. than needed. A lack of data scientists is causing an increase in demand for the profession. Compared to engineers and chartered accountants, India will require over 200,000 data scientists by 2018. Now is the time to join them and become in demand.

2. Unbeatable salaries:- Glassdoor estimates that, data science was the highest paid field. Their research shows that the national average salary for a Data Scientist is 50,000 in Europe and £125,000 in the United States. In India, the national average salary for a Data Scientist is INR 6,50,000 and in the United States it is $1,20,931. Salary is significantly higher than that of other jobs.

3. Value-added services help businesses succeed:- Their growth is evident in many fields of business, including IT, health-care, E-commerce, and marketing. A Data Scientist serves as the most valuable asset of the company and serves as an adviser and strategic partner for the management team. Their goal is to harvest valuable insights that can aid in refining their niche, identifying the best target audience and managing future marketing plans and growth strategies.

4. An ever-changing field:- The growth of data all over the world has accelerated the development of Data Science. Organizations can leverage the skills of data scientists to make better strategic decisions by leveraging data and information. To come up with the most suitable solutions for the businesses, they get the opportunity to work with and experiment with data. Data Science is emerging with new technologies that are leveraging many new practices and techniques, including Big Data, Artificial Intelligence (AI), Machine Learning (ML), Blockchain, Serverless Computing, Digital Twins, and more.

5. Getting a job is easy:- Currently, the most demanding job is data science, it is flourishing. Data Scientists are in high demand by companies. There is a shortage of Data Scientists, as demand is high. In fact, Data Scientists are now being hired by companies from a wide range of industries, from e-commerce to start-ups. Data Science is now essential to many start-ups, and is not found only in e-commerce.

Types of Data Science Skills:

Data scientist skills can be categorized as follows:

1. Technical Skills:- Whether it is statistics, probability, algebra, or whatever, math is fundamental for data science. We can determine whether a pattern exists in the data we collected through statistics. For every set of data, we can say that a mean and variation is necessary. Whether something is likely to happen or not, probability predicts its future. As data revolves around functions and equations, linear algebra is at the core of data science. Data could also be converted into vectors and matrices, which is crucial to linear algebra. Mastering linear algebra is an important part of becoming a data scientist. When you love mathematics, you'll be able to achieve great things.

2. Programming Skills:- A statistician no longer analyzes a company's sales with pen and paper or uses a calculator to benchmark the sales of a competitor. With programming, we now have the ability to do all these things, and more than those. In the long run, we can see what the data suggests, whether it was consistent in the past, and what we are doing now. Data science is best done with Python and R programming languages. The simplicity and straightforward style of Python makes it impossible to go back to other programming languages once you've learned it. Assume that two people are speaking a language they are both familiar with. In some cases, one may need to draw a sketch to explain exactly what is meant. Python enables us to do that. For the programs, there is no interaction with header files. Whenever you feel that your problem is complicated, there are libraries assigned to handle it for you. Consider them finished once they are imported. A programming language like R is for people who have no prior knowledge of a programming language. You are more likely to succeed than you think. When more sketches are needed, R is mostly used. In the beginning, it can be beneficial to become fluent in two languages at once but to gain proficiency in one can be more beneficial.

3. Ability to visualize:- Visualizing the data patterns is essential to creating graphs. Excel is an excellent tool used to draw graphs and charts according to our needs. In addition to Tableau, Infogram, and Datawrapper, other tools are available for data visualization. Various tools are available to assist us when we become lost in a large sea of information. In order for us to present data to management and draw conclusions, data, however big or small, is essential.

4. Communication Skills:- In either case, it is imperative to communicate our findings to a group of teammates or to upper management. Communications allow us to reach a level higher than what really matters. It is important to be a good communicator in order to share our ideas and to identify discrepancies in the data. It is most important to show the findings of data and plan the future with presentation skills. Presenting a message effectively during the presentation involves looking each other in the eye. Nonetheless, it appears that people don't learn this skill while preparing to be in data science. People, this skill is not the last one to learn but a skill to be walked through while learning other skills. A blowing conclusion to the problem looks amazing after performing the mathematics calculations. In programming, comments between lines of code are recommended so that anyone reading the code understands it better. A visualization tool can only be completed when it is titled properly and explained properly. Therefore, data scientists need to have excellent verbal and written communication skills.

Career path for Data Science:

In view of the significance of data and its growing every second, it is not a surprise that Data Science Careers offer many opportunities for professionals. Having been involved in multiple fields throughout the career, it combines several different roles. Programmers, analysts, statisticians, etc., can be involved in Data Science. Data Science has a lot of opportunities these days because of the massive amount of data and the need to analyze it, which provides a great deal of value to businesses. Those seeking careers in Data Science include Business Intelligence Analysts, Data Analysts, Data Mining Engineers, Data Architects, and Data Scientists, among others. As Business Intelligence Analysts, you will be expected to analyze data and mine data in addition to understanding business functions. In order to improve the organization's position, Business Intelligence Analysts analyze its data to figure out the data patterns. Using programming languages and analytical tools, data analysts analyze raw data in order to produce meaningful results. The main responsibility is to clean and maintain data, and then analyze and present the data. An Engineer who specializes in Data Mining analyzes data for their organizations and for the third parties they interact with using advanced algorithms. Working with designers, developers, and users, Data Architects design the blueprints for integrating and maintaining data sources. A Data Scientist identifies the trend by examining a large volume of data to carry out further analysis. Providing a deeper insight into the data is achieved through this approach. Scientists analyze the data, understand it, and analyze complex business problems with both IT and Business.


As the data volume grows, the career path of Data Science will become increasingly important as it will be necessary to analyze the data. Data Scientists are in high demand globally, and the average salary for these professionals is approximately 10,000 per year (US). Organisations also benefit from Big Data, as data scientists add value to the data. Since there are a high number of professionals seeking careers in Data Science, salaries for these professionals will remain high.

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Key Features

ACTE India 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 India
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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Hands-on Real Time Data Science Projects

Project 1
Sign Language Recognition project

Our project aims to bridge the gap between the speech and hearing impaired people and the normal people.

Project 2
Loan Prediction project

The main objective of this project is to predict whether assigning the loan to particular person will be safe or not.

Project 3
Store Sales Prediction project

A sales forecast aims to predict future sales and is used as the basis of planning time and resources.

Project 4
Detecting Parkinson’s Disease project

To build a model to accurately detect the presence of Parkinson's disease in an individual.

Our Best Hiring Placement Partners

ACTE India Position helps more than 1000+ understudies each year. Our restrictive situation cell will unmistakably  zeroing in on Understudies Positions. Our talented understudies acted in all meetings and they convey what the organizations are searching for and accomplish their vocation start without any problem.
  • We give unique student placement portal where you will find all of the interview schedules and be notified via email.
  • We offers a different understudies entrance for procedure with free acknowledgment and provide study material.
  • We are related with top affiliations like Google, CTS, TCS, IBM, etc it make us arranged to place our understudies in top MNCs across the globe.
  • After successful completion of the training, ACTE provides F2F interaction, interview preparation and 100% placement help to qualifying applicants.
  • During the party, suggesting this master accomplishment confirmation on student continue has a huge impact and makes the reliability of understudy likewise upgrades it's anything but's a more sweeping level of work openings.
  • We will schedule Mock interviews and group discussions were held every week to find out the GAP in Candidate Knowledge

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.

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About Adequate Data Science  Instructor

  • Our Data Science Training in India. Our Data Science Training in India is all through found a few solutions concerning being understudy related with and finishing activities to hit cutoff times and targets.
  • The accomplices will outfits both speculative and reasonable information with trustworthy endeavor works.
  • Our guides are industry topic prepared experts and subject experts who have appreciated running applications giving best Data Science training to the learners.
  • Our tutors offer immovable freedom to the applicants, to investigate the subject and learn reliant upon steady models. Our guides help the rivals in completing their endeavors and incredibly set them up for requests questions and answers. Contenders are permitted to address any requesting at whatever point.
  • Trainers are also help candidates increase your chances of being hired by showcasing your real time project experience and Internal Hiring process.
  • From learning entrance coordination to contextualized substance and learning ways, we're founded on your thriving.

Data Science Course Reviews

Our ACTE India 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 did Data Science.I learnt many things because of trainers good .from day by day I improved a lot They clear all doubts and I felt happy to join ACTE in India. I met some fantastic people and I’m very impressed. It was the best place for me to The support me here.


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

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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
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  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Data Science training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Data Science Course At ACTE?

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