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Data Science Training in Mumbai

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Weekdays Regular

08:00 AM & 10:00 AM Batches

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


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(10:00 AM - 01:30 PM)

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

  • During the course, students learn to analyze data from different sources, learn machine learning techniques, and learn statistics.
  • Following this section, students will learn about the roles and skills involved in data science. In addition, you will learn the ins and outs of customizing your data to exactly the audience you are reaching.
  • In this section, various methods of data analysis will be discussed. In the area of data science, projects are carried out using a variety of execution, planning, and presentation methods. With these tools and techniques, you can maximize your business's data.
  • Through out this course, you will develop a thorough understanding of data science. Data Scientists, Data Engineers, and Product Analysts are among the many fields covered in this lecture.
  • This course will teach you how to gather and analyze data using tools like R, Python, and command line. Among other topics, we will discuss A/B testing and market analysis.
  • The event this year will be attended by a number of well-known technology companies, such as Amazon, Square, Facebook, Microsoft, Google, and Airbnb.
  • As well as quizzes, the course provides explanations and solutions to each question. Besides assisting you in preparing for exams, you will also find the program useful in the workplace.
  • Before you go for an interview, it may be beneficial to be familiar with the following topics.
  • Students will gain a comprehensive understanding of the subject matter through this curriculum. Our programs include preparing students for job interviews and training them for employment, as well as providing them with opportunities to work in reputable organizations.
  • 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

It is necessary to have a bachelor's degree in mathematics, statistics, computer science, or data science. Any bachelor's degree engineering subject is acceptable. If you meet these requirements, you are eligible to participate in this course.
This hybrid program will need you to attend 184 hours of classroom sessions spread out over four months. You will have access to the online Learning Management System for recorded videos and assignments for another three months following completion. It will take 150 hours to accomplish all of the online assignments. Aside from that, you'll work on a genuine project for a month.
This course covers a variety of topics, including Python and R programming.
  • Investigate the information you've gathered thus far.
  • Inference from Statistics
  • Probability Distributions
  • Data Visualization Hypothesis Testing
  • Learning based on data exploration that is supervised
  • Predictive Modeling
Experience with real-time data science projects will be an advantage, as major businesses don't often appreciate freshers for these roles. Our Data Science course focuses on addressing both core curriculum and real-world business problems. Our real-world projects will help you get a solid grasp of the field and prepare you for Data science job interviews with top companies. Our teachers are willing to share their experiences and help you with period issues. You must finish either online or classroom training to launch a career in Data Science.
Python, Perl, C/C++, SQL, and Java are among the programming languages you'll need to know, with Python being the most often utilized commitment to writing language in Data Science jobs. These programming languages make managing vast volumes of unstructured data easier for data scientists.
  • In most cases, the curriculum is based on the most recent industry standards. To assist you to acquire a deeper understanding of the subject, our teachers give real-time training using live projects.
  • We provide training in several forms, including online, in the classroom, and weekend sessions.
  • Our training program is very customizable to your on-the-job needs.
  • Our Data science course may help you crack related interviews at top MNCs since our specialists can assist you through the process by sharing their real-life experiences in relevant areas.
  • The Data Science role necessitates expertise, Data Science knowledge, as well as the use of relevant tools and technology.
  • Professionals in Information Technology
  • Professionals in Banking and Finance
  • Managers of Marketing
  • Managers of Analytics

Will I get the Placement training for a Data Science course?

The course was created to give students a head start in the fields of information science and machine learning. Students who finished the course have gone on to work at prestigious analytics businesses as Data Scientists, Machine Learning Engineers, Data Analysts, Analytics Experts, and other jobs.

Is it worthwhile to pursue a career in data science?

For several reasons, data science is one of the most popular career options in the twenty-first century. For many people, the necessity for this technology and its scope are the primary motivators for pursuing a career in it. Furthermore, the pay scale offered in this area is piquing the attention of young individuals to work as Data Scientists. The job opportunities in this area are frequently rated as among the best-paying in the country. As data science continues to extend across numerous fields, many current job roles are expected to be displaced. As a result, anyone looking for long-term employment should choose data science.

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

  • There are several intriguing job opportunities in this sector. A large number of young people want to work in these professions in the future. Let's take a look at some of the most sought-after Data Science positions.
  • Data Analyst.
  • Statistician Business.
  • Analyst Database.
  • Administrator.
  • Data Engineer.
  • Data Scientist.

What are the job responsibilities of a Data Scientist?

  • Identifying and automating useful data sources.
  • Pre-process both organized and unstructured data.
  • Analyze huge amounts of data to find trends and patterns.
  • Create predictive modeling models and algorithms using machine learning.
  • Models are combined by a modeling set.

What are the prerequisites to learn this Data Science course?

Professionals who want to thrive in this course should have the following skills:
  • Basic statistical expertise is required.
  • Any language's fundamental understanding.
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Overview of Data Science Training in Mumbai

The best knowledge human training in metropolis offers one among the foremost advanced certification courses that embrace numerous elements like Machine Learning, cluster analysis, data processing, cleansing, transformation, and deploying knowledge visualization, among others. It offers the most exhaustive course on data sciences, which covers complete concepts from the field of data collection, data mining, data collection, data purification, data exploration, data transformation, data engineering, data integration, data mining, building prediction models, visualization of data and customer solution deployment in Jaipur. Data science training in Mumbai Skills and techniques spanning from statistical analysis, text mining, regression modeling, testing of hypothesis, predictional analysis, and analysis, machine learning, depth learning, natural language processing, predictive modeling, R Studio, Tableau, Spark, Hadoop, R programming languages.

Additional Info

What is DataScience :

Data science is an associate knowledge base field that uses scientific ways, processes, algorithms, and systems to extract data and insights from structured and unstructured information, and apply data and unjust insights from information across a broad variety of application domains. information science is expounded to data processing, machine learning, and large information.

As part of this data science program, Python is covered extensively. It has more than 400 participants in several international enterprises, including E&Y, Panasonic, Accenture, VMWare, Infosys, IBM, etc., providing the best data science training in Jaipur, considered to be the best in the industry and to offer training services from training to placement as part of the Data Science training program.

Advantages of Data Science :

  • It’s in Demand :

    Data Science is greatly in demand. Prospective job seekers have varied opportunities. it's the quickest growing job on Linkedin and is foretold to form eleven.5 million jobs by 2026. This makes information Science an extremely employable job sector.

  • Abundance of Positions :

    There are only a few that have the desired skill-set to become an entire information man of science. This makes information Science less saturated as compared with different IT sectors. Therefore, information Science may be an immensely superabundant field and incorporates a heap of opportunities. The sector of knowledge Science is high in demand however low in supply of knowledge Scientists.

  • A extremely Paid Career :

    Data Science is one of the foremost extremely paid jobs. In step with Glassdoor, information Scientists create a mean of $116,100 per annum. This makes information Science an extremely remunerative career possibility.

  • Information Science is flexible :

    Their area unit varied applications of knowledge Science. It's widely employed in health-care, banking, practice services, and e-commerce industries. Information Science may be a versatile field. Therefore, you may have the chance to figure in varied fields.

  • Information Science Makes information higher :

    Companies need delicate information Scientists to use and analyze their information. They did not solely analyze the info however additionally improve its quality. Therefore, information Science deals with enriching the information and creating it higher for his or her company.

  • Information Scientists area unit extremely Prestigious :

    Data Scientists enable firms to form smarter business selections. firms trust information Scientists and use their experience to produce higher results for their shoppers. This provides information Scientists a crucial position within the company.

  • No additional Boring Tasks :

    Data Science has helped varied industries to alter redundant tasks. firms area unit victimization historical information to coach machines to perform repetitive tasks. This has simplified the arduous jobs undertaken by humans before.

  • Information Science Makes product Smarter :

    Data Science involves the usage of Machine Learning that has enabled industries to form higher products tailored specifically for client experiences. For instance, Recommendation Systems utilized by e-commerce websites offer personalized insights to users to support their historical purchases. This has enabled computers to grasp human behavior and create data-driven selections.

  • Information Science will Save Lives :

    The Healthcare sector has been greatly improved owing to information Science. With the arrival of machine learning, it's been created to make it easier to notice early-stage tumors. Also, several different healthcare industries unit victimization information Science to assist their shoppers.

  • Information Science will cause you to a more robust Person :

    Data Science won't solely provide you with a good career however it will also assist you in personal growth. you may be able to have a problem-solving angle. Since several information Science roles bridge IT and Management, you may be able to fancy the simplest of each world.

The Various Career oppournities 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, maschine 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 analyse 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 visualisation. Machine learning skills and an in-depth grasp of cloud platforms like Azure, IBM and Google are the main goals.

3. Data Engineer:- Traditionally, organisations hire and manage data everyday 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 organisation 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.

Skills Required for Data Science :

  • crucial thinking
  • Effective communication
  • Proactive downside finding
  • Intellectual curiosity
  • Business sense
  • Ability to organize information for effective analysis
  • Ability to leverage self-service analytics platforms
  • Ability to put in writing economical and rectifiable code
  • Ability to use scientific discipline and statistics fitly
  • Ability to leverage machine learning and AI (AI)

Tools for Data Science :

1. Tensorflow :

Focused on deep learning, launched by Google, Tensorflow has 153k stars on GitHub.

2. PyTorch :

Open supply, in-built Python, asterisked by ±45k in GitHub. Most information science groups that I in person apprehend trust PyTorch which has libraries for many machine learning approaches.

3. Rapidminer :

Rapidminer is made in 3 major parts. RapidMiner Studio is the Visual workflow Designer for information Science groups The platform makes it doable to induce visibility into information science cooperation and governance. RapidMiner Radoop removes the quality of knowledge school assignments and machine learning on Hadoop and Spark. The platform is employed in several industries with differing kinds of solutions.

4. DataRobot :

DataRobot offers a machine learning platform for information scientists of all ability levels to make and deploy correct prophetical models in a very fraction of the time it is accustomed to taking. The technology addresses the essential shortage of knowledge scientists by ever-changing the speed and social science of prophetic analytics. It searches through legion doable mixtures of algorithms, pre-processing steps, features, transformations, and calibration parameters to deliver the simplest models for your dataset and prediction target.

5. Alteryx :

End-to-end analytics platform that empowers business analysts and information scientists alike to interrupt information barriers and deliver game-changing insights that are determined business issues. The Alteryx platform is self-serve, click, drag-and-drop for many thousands of individuals in leading enterprises everywhere on the planet.

6. Qubole :

Qubole is smitten by creating data-driven insights simply accessible to anyone. Customers have chosen Qubole as a result of our tendency to create the industry’s initial autonomous information platform. This cloud-based information platform self-manages, self-optimizes and learns to enhance mechanically and as a result delivers unbeatable light soreness, flexibility, and TCO. Qubole customers target their information, not their information platform. Qubole investors embrace CRV, Lightspeed Venture Partners, Norwest Venture Partners, and IVP.

7. Paxata :

Paxata is the pioneer in showing intelligence empowering all business customers to remodel data into prepared info, instantly and mechanically, with an associated intelligent, self-service information preparation application designed on a climbable, enterprise-grade platform supercharged by machine learning.

8. Trifacta :

Trifacta’s mission is to make radical productivity for those who analyze information. they're deeply centered on determining the most important bottleneck within the information lifecycle, information wrangle, by creating a lot of intuitive and economical for anyone United Nations agency works with information. Their main product is the Wrangler.

9. Lumen Data :

LumenData could be a leading supplier of Enterprise info Management solutions with deep experience in implementing information persistence layers for information mastering, prediction systems, and information lakes similarly as information Strategy, information Quality, Information Governance, and prophetical Analytics.

10. Feature Labs :

Feature Labs could be a prophetical analytics platform created to create information science automation, a strategic element of any organization. By victimization Feature Labs, groups will utilize machine learning and computer science to deploy new products or services, determine essential insights, and perceive what their information says concerning the long run of their business.

Role and Responsibilities Of DataScience :

  • Work with stakeholders to work out a way to use business knowledge for valuable business solutions
  • Search for ways in which to induce new knowledge sources and assess their accuracy
  • Browse and analyze enterprise databases to change and improve development, promoting techniques, and business processes
  • Create custom knowledge models and algorithms Use prognostic models to boost client expertise, ad targeting, revenue generation, and more.
  • Develop the organization’s take a look at the model quality and A/B testing framework
  • Coordinate with varied technical/functional groups to implement models and monitor results
  • Develop processes, techniques, and tools to investigate and monitor model performance whereas guaranteeing knowledge accuracy

Payscale :

An entry-level Data Scientist, IT with less than 1 year experience can expect to earn an average total compensation (includes tips, bonus, and overtime pay) of 573 based on 38 salaries.

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Key Features

ACTE Mumbai 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 Mumbai
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
Handwritten Digit Recognition Project

The aim of this project is to implement a classification algorithm to recognize handwritten digits (0- 9). It has been shown in pattern recognition that no single classifier.

Project 2
Driver Drowsiness Detection Project

The main aim of this is to develop a drowsiness detection system by monitoring the eyes; it is believed that the symptoms of driver fatigue can be detected early enough.

Project 3
Survival Prediction on the Titanic Project

The goal of the project was to predict the survival of passengers based off a set of data. We used Kaggle competition to retrieve necessary data and evaluate accuracy.

Project 4
Time Series Modelling Project

There are two main goals of time series analysis is to identifying the nature of the phenomenon represented by the sequence of observations, and forecasting.

Our Best Hiring Placement Partners

ACTE Mumbai educational plan is intended to train you apparatuses and abilities that are valuable when you land into position positions.
  • ACTE putting together subject/space explicit specialized abilities preparing by specialists. profession advising for seeking after higher investigations and give placement guidance.
  • Applicants directing to cause them to comprehend the assurance of life and Train them to run after the objective and placed in top Mncs.
  • We support our understudies to confront the difficulties of the determination interaction by directing intermittent general fitness tests, specialized inclination tests, bunch conversations, mock meetings and so forth, and making them by and large mindful of the mechanical situation and so on
  • ACTE Adequately doing organize industry-cooperation as far as shared contacts, trade of data and thoughts, orchestrating visits and specialized discussions from Placement specialists, and so forth
  • We arise as an innovator in situation where multinationals strive with one another to enlist Learners.
  • Our placement team fabricate a main HR place to sharpen the abilities of applicants in innovation, trustworthiness, correspondence, scientific capacity, mechanical mindfulness and assist them with being worldwide parts in IT and related businesses.

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

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About Satisfactory Data Science Mentor

  • Our Data Science Training in Mumbai. In our virtual homeroom, coach permits applicants can raise their questions and have conversations with different members also. The learner feels as though he/she is in a genuine homeroom.
  • Through the execution of a 24X7 live framework and a power of in fact adroit experts, we are available to help you in any period of your task. We offer a need-based, on-request, on schedule and inside spending project support direction and not simply an outline of linguistic structure and strategies.
  • Our mix of infrastructural strength and demonstrated showing models on different courses has assisted numerous Learners with achieving their vocation objectives.
  • We give project preparing demonstrated industry principles and our programming experts who are intending to change their s/w area are given various degrees of openness in the venture advancement life cycle with center information in documentation, improvement, establishment and design of the created undertaking alongside coding and advancement norms in Data Science.
  • Our profoundly mentor will loan highlight point direction in finishing of the undertaking task. on the off chance that learner hand over the specialized particulars, our expert specialized group will do learner job well inside the specified time.
  • Trainer to help the advancement of learner with adjusted arrangement of specialized abilities, relational abilities and with an uplifting outlook to placement career.

Data Science Course Reviews

Our ACTE Mumbai 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 finished my Data Science classes in Mumbai.Good Atmosphere to learn and very good communication between the center, trainer and us. Good in arranging sub trainer in case current trainer is not available. Over all good place to learn Data Science in ACTE.


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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  • 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
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