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Data Science Course in Hyderabad

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07- Dec - 2022

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Get Trained with Our Effective Data Science Training in Hyderabad

  • We Provide Well Organized and Structure Course Upon completing the requirements and maximum knowledge of the Data Science Program with the support of our highly-skilled training team.
  • Well Equipped Infrastructures with Excellent Lab Facilities, Placement Assistance, 24/7 Experts Support, and versatile timings.
  • Get to learn trending updates and Machine Learning Algorithms, NLP Concepts, Data Visualization with Tableau, and IBM Hackathons in the Data Science Program from the Experts.
  • Experience with Hand-on live project sessions and Able to work on projects independently and integrate them on new trending technologies to build an end-to-end application.
  • With Data Science Certification Course you will gain in-depth knowledge on Data Science, real-time analytics, statistical computing, SQL, and Parsing machine-generated Data.
  • Our Professional tutors will assist the learners to understand each part of the Data Science Program, from Beginning to Advanced.
  • 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

Python has to have the most common language writing commitment needed in the data science positions, including Python, Perl, C/C++, SQL, and jaw. These languages facilitate unstructured information sets for data scientists.
  • The curriculum is usually designed according to the latest commercial requirements.
  • Our teachers give live instruction in real-time to help you gain a deeper grasp of the subject.
  • We provide training in several ways, e.g. online, weekdays and weekends.
  • Our training program is highly multifaceted to suit your timings in the market.
  • Our data sciences course can help you do crack-related interviews at primary MNCs since our teachers can coach you throughout the process by sharing their experience in relevant domains in real-time.
A merger of experience, data science, and the right tools and technology are essential to play the function of data science.
  • IT Professionals
  • Banking and Finance Professionals
  • Marketing Managers
  • Analytics Managers
  • Freshers
  • There is a lot of information in all areas of medical care and so there is a rising requirement for people from data sciences who will appreciate and extract intentional insights.
  • The gap between demand is enormous and there are plenty of chances for work and play.
  • Intended to be the finest data scientist in the employment market.
Your professional objectives and your amount of money and time to spend on your education decide the time it takes to become a data scientist. There is a bachelor of science degree in four years and boot camps for three months. You may wish to pursue a master's diploma in as little as one year if you already have a bachelor's degree or have finished a Bootcamp. The majority of data scientists have a degree, according to the Burtch Works Study.
Data is the future. In the next few years, data science will have a bright future and data scientists will also be successful in their careers. In the numerous sectors in which it has been used, data science has had a major influence. In addition to displacing many current occupations, data science should extend its expertise to many other industries and generate new dynamics. About 1 lakh of jobs in the field of data sciences are available on this planet for diverse vocations.
Consider some of the key jobs in the field of data science.
  • Data Analyst.
  • Statistician Business.
  • Analyst Database.
  • Administrator.
  • Data Engineer.
  • Data Scientist.

What is the typical salary of a certified data Scientist?

This domain of data science claims to be one of the country's top-paid jobs. Annual pay is estimated at 8.2 lakh for a data scientist in India. The annual wage is between 6 and 20 lakhs. In India, more than 40 thousand jobs are available in the area of data science for different vocations. Great Learning offers India's finest in data science and work placements.

What are the job responsibilities of a Data Scientist?

  • Identification and automation of valuable data sources.
  • Conduct structured and unstructured data pre-processing.
  • To uncover trends and patterns, analyze massive volumes of information.
  • Create machine learning models and algorithms for predictive modeling.
  • Combine models by modeling set.

What are the tools covered in a data science certification training?

  • R.
  • Python.
  • BI Tools And Applications.
  • Jupyter.
  • BigML.
  • Domino Data Lab.
  • SQL Consoles.

What are the prerequisites to learn this Data Science training in Hyderabad?

Professionals who desire to excel in this course should have:
  • Basic statistical knowledge
  • Fundamental comprehension of any language

Is data science easy to learn?

Data science is an enormity, and within six months or one year, people cannot obtain skills. The learning of data science involves technical expertise together with basic programming knowledge and analytical tools to begin. However, this Data Science course covers from start all important topics, so that you may easily utilize your new abilities.
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Overview of Data Science Course in Hyderabad

This course enables you to master data analysis, company analysis, data modelization, machine learning methods, k-means clustering, Naïve Bayes, etc. This Data Science Training in Hyderabad program will assist you to master R statistical computing, developing an e-commerce recommendation engine, proposing films, and implement market basket analyses in retail. Get top data scientists to get the best online data science courses. Provides the most thorough and in-depth training in data scientists. The courses are prepared with comprehensive feedback from specialists in the business. You can manage many components including data analysis, mining, purification, data transformation, algorithms for machine learning, and much more in order to gain vital information about the business.

Additional Info

What is Data science?

Data science continues to develop as one of the skilled professionals' most promising and demanding careers. Today, successful data professionals recognize that they need to enhance the traditional ability to analyze vast quantities of data, explore data, and program. Data scientists have to grasp the entire spectrum of the data science life cycle and have a degree of flexibility and comprehension in order to optimize their revenues in each step of the process, in order to find usable intelligence for their organizations.

Who Should Take This Course :

    The position of Data Science involves a mix of expertise, knowledge of data science, and suitable technologies and instruments. For both new and experienced workers, it is a strong career choice.

    The Data Scientist Course in London is best suited to aspiring professionals from all backgrounds in analytical studies including :

  • Professionals in IT.

  • Chefs of Analytics.

  • Analysts of business.

  • Professionals of banking and finance.

  • Administrators of marketing.

  • Network Manager Supply Chain.

  • Bachelor or Master of Arts Students or Recent Graduates.

Required Skills for Data Science :

1. Statistical analysis :

Identify patterns in information. This involves a strong sense of pattern recognition and detection of anomalies.

2. Machine learning :

Implement algorithms and applied math models to change a laptop to mechanically learn from knowledge.

3. Computer science :

Should Apply the principles of computing, information systems, human/computer interaction, numerical analysis, and package engineering.

4. Programming :

Write pc programs and analyze giant datasets to uncover answers to complicated issues. information scientists have to be compelled to be comfy writing code operating during a type of languages like Java, R, Python, and SQL.

Roles and responsibilities :

Data Engineer :

Data engineers square measure accountable for coming up with, building, and maintaining knowledge pipelines. They have to check ecosystems for the companies and prepare them for knowledge scientists to run their algorithms. Data engineers additionally work on instruction execution of collected knowledge and match its format to the keep knowledge. In short, they create a positive that the info is prepared to be processed and analyzed. Finally, they have to stay the scheme and therefore the pipeline optimized and economical and make sure that {the knowledge|the info|The information} is accessible for data scientists and analysts to use.

Database Administrator :

Sometimes the team coming up with the info and therefore the one exploitation is different. Currently, several firms will style an info system that supports specific business needs. However, the info's management is completed by the corporate shopping for the database or requesting the look. In such cases, every company hires an individual or several 1 to be to blame for managing the info system. An info administrator is to blame for observing the info, ensuring it functions properly, keeping track of the info follower, and building backups and recoveries. They are added to blame of granting {different|totally different|completely different} permissions to different workers supported their job needs and employment level.

Machine Learning Engineer :

Machine learning engineers are on-demand these days. they have to be aware of the varied machine learning algorithms like a bunch, categorization, and classification and are up-to-date with the newest analysis advances within the field. To perform their job properly, machine learning engineers ought to have sturdy statistics and programming skills additionally to some data of the basics of software system engineering. In addition to coming up with and building machine learning systems, machine learning engineers ought to run tests like A/B tests and monitor the various systems' performance and practicality.

Data Scientist :

Let’s begin with the foremost general role, information human. Being an information human entails, you'll traumatize all aspects of the project. ranging from the business aspect to information grouping and analyzing, and at last visualizing and presenting. A data human is aware of a touch of each thing; every step of the project, thanks to that, they will provide higher insights on the simplest solutions for a selected project and uncover patterns and trends.

Moreover, they'll be to blame for researching and developing new algorithms and approaches. Often, in huge firms, team leaders blame individuals with specialized talents area unit information scientists; their skill set permits them to overlook a project and guide them from beginning to end.

Technology Specialized :

Data science remains a developing field; because it grows, additional specific technologies can emerge, like AI or specific milliliter algorithms. Once the sector develops therein manner, new specialized job roles are going to be created, for example, AI specialists, Deep Learning specialists, IP specialists, etc. These job roles apply to knowledge scientists and analysis in addition. as an example, transportation DS specialist, or selling storyteller, and so on. Such job roles are going to be explicit on the responsibilities it entails and can loosen the final mortal and engineer's work.

Business Intelligence Developer :

Business Intelligence developers additionally referred to as Bi developers are guilty of planning and developing ways that permit business users to seek out the data they have to create selections quickly and with efficiency Aside from that, they additionally got to be comfy mistreatment new Bi tools or planning custom ones that offer analytics and business insights to know their systems higher. BI developer’s work is usually business-oriented; that’s why they have to possess a minimum of a basic understanding of the basics of business models and the way they're enforced.

Skills You Will Gain in this Course :

  • Gain a thorough knowledge of data structure and data management Comprehension and application of linear or nonlinear regression models and data analysis classification procedures.

  • Know the various components of the Hadoop ecosystem.

  • Deep grasp of supervised and unmonitored learning models like linear regression, logistic regression, clustering, reduction in dimensionality, K-NN, and pipeline.

  • Computing Science and technology using SciPy packages, including integrate, optimize, statistics, IO, and weave.

  • Get knowledge with NumPy and Scikit-Learn programs for the mathematical computer.

Top Tools of Data Science :

Some of the major tools of Data science :

1. SAS :

It is one of those data scientific instruments designed strictly for applied math functions. SAS is a proprietary closed-source software package for analyzing data by huge firms. For applied math modeling, SAS utilizes basic SAS language programming. It's ordinarily utilized in business software packages by specialists and businesses. As a knowledge human, SAS provides multitudinous applied math libraries and instruments to model and organize knowledge. Although SAS is extremely trustable and has robust support, it's high in value and used solely by larger industries. Moreover, many SAS libraries and packages don't seem to be within the base package and maybe upgraded costly.

2. Apache Spark :

Apache Spark, or just political Spark could be a powerful analytics engine and therefore the most typically used knowledge Science instrument. Spark is meant specifically for batch and stream processes. Several genus Apis permit data scientists to access machine learning data, SQL storage, etc., repeatedly. It improves over Hadoop and is one hundred times faster than Map-Reduce. Spark has several Machine Learning genus Apis that facilitate knowledge scientists to predict the data.

Spark will manage streaming data higher than different huge knowledge platforms. Spark will method data in the period compared to different analytical tools that solely method historical data in batches. In Python, Java, and R, Spark provides many genus Apis. However, Spark’s most robust combination with Scala could be a virtual Java-based programming language, that is cross-platform in nature.

3. Excel :

The Data Analysis instrument is most likely most typically used. surpass is formed principally to calculate sheets by Microsoft and is presently normally used for processing, sophisticated, and image calculations. surpass is AN economic knowledge science analytical instrument. surpass still packs a punch whereas it’s the standard data analysis instrument. surpass has many formulas, tables, filters, slicers, and so on. you'll conjointly generate your personalized options and formulae with surpassing. whereas surpass continues to be a perfect possibility for powerful knowledge images and tablets, it's not meant to calculate vast quantities of knowledge. You also will connect SQL to surpass and use it for knowledge management and analysis.

4. D3js :

Javascript is usually used as a scripting language on the shopper-facet. D3.js, you'll be able to produce interactive visualizations on our application through the Javascript library. With numerous D3.js APIs, you'll be able to build dynamic viewing and information analysis in your browser exploitation numerous options. The utilization of animated transitions is another robust characteristic of D3.js. D3.js dynamically permits customer-side updates and actively reflects the visual image on the browser through data modification. This could be combined with CSS to supply illustrated and temporary visualizations to help you to execute tailored graphics on web content.

The Future of Data Science :

    Having detailed the construct of knowledge science, it's pertinent to contemplate bound factors that demonstrate the nice potentiality evident within the way forward for information science. These factors justify the explanations why modern businesses and organizations can and have begun to appear to the positive future information science holds for them.

  • Companies Inability to Handle Data :

    Every minute, completely different businesses and organizations perpetually gather knowledge for his or her various transactions. However, the matter is that almost all of those organizations share a typical challenge; that is analyzing and categorizing the info that has been gathered and kept. Thus, in such dire things, the sole resolution for the businesses in the service of a knowledgeable man of science. With properly dead knowledge science, these organizations can increase productivity through adequate and skilled handling of knowledge. Indeed, in the long run {knowledge|knowledge of information} science can bring an answer to companies’ inability to effectively handle data.

  • Virtual Reality Will Be Friendly :

    Without a doubt, everywhere on the planet, there's an associated upsurge within the contributions of computing, and lots of businesses square measure counting on it. With the introduction of modernized and advanced ideas like Neutral Networking and Deep Learning, massive information prospects are guaranteed to flourish with these current innovations. In nearly every ramification of life, machine learning is presently being introduced and used. In addition, VR – computer games and AR – increased Reality, square measure passing through nice biological processes.

  • Revised Data Privacy Regulations :

    The reality is that a lot of and a lot of folks square measure workout increasing caution and application once it involves sharing their knowledge with businesses. an outsized share of people square measure skeptical concerning dropping an explicit degree of management to corporations. This can be merely a result of the rise within the awareness of information stealing and its negative effects. Thus, reputable corporations square measure sensitive and deliberate to keep their clients’ info safe and intact.

    To buttress this, the GDPR – General knowledge Protection Regulation, was lapsed by the state of the EU Union in might. It has conjointly been reportable that such regulation for knowledge protection shall once more lapse in California in 2020. Hence, with the recent Revised knowledge Privacy rules going down, the longer-term of information science is incredibly bright.

Benefits of Data Science :

    The Data Science career is in high demand And there's an abundance of opportunities within the field. It's aforementioned that India is the second largest in recruiting folks with knowledge of Science skills, once the USA.

  • The compensation is tight because it may be a career in demand. The national average wage of an information human in India is around 9Lakhs every year.

  • As the applications of knowledge Science square measure versatile because it is being employed by E-Commerce firms, Medical, and pharmaceutical company industries, Web-based businesses, monetary and Banking sector, Consulting firms, to administer some examples.

  • So, an individual will build a career in their space of interest or a sector wherever he/she has previous expertise. Data Science may be a secure career alternative. The necessity for knowledge Scientists exists as long as knowledge exists.

Pay scale of Data Scientist:

The additional responsibilities and expectations of operating abstractly in an exceedingly huge scale quantity to pay over double that of an information analyst. According to the Salary Report, the data scientist's median salary is Rs. 94 Lakhs, data scientist has a very comprehensive job.

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Key Features

ACTE Hyderabad 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 Hyderabad
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 about Real-Time Data Science Projects

Project 1
Detecting Parkinson's Disease Project.

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

Project 2
Road Lane Line Detection Project.

In this project, lines placed on the road provide lane detection instructions to a human driver and detections.

Project 3
Driver Drowsiness Detection Project.

The major goal of this project is to detect when a driver may become tired and fall asleep while driving.

Project 4
Fake News Detection Project.

The goal of this project is to create a real-time machine learning model determine the legitimacy of social news.

Our Top Hiring Partner for Placements

Arrangement Backing is probably the best assistance offered by ACTE. Upon fruitful finish of any course from our foundation we help the trainess to land their fantasy position by giving situation help.
  • Data science mentors at ACTE guides the understudies in resume building and urges the understudies to take up the meeting by giving normal counterfeit meeting test meetings.
  • Acte has restricted with 150+ organizations to give occupations to numerous learner.
  • A committed arrangement cell for the members who finished the course.
  • We are giving individual students entrances to position and, you may get all the meeting plans on it.
  • Our position group will moreover imply the applicants about the stroll in meeting.
  • We related with a committed position support group that executes the requirements of understudies on employing.

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 the successful completion of our Data Science online training and practical-based projects.
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

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

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About Experienced Data Science Trainer

  • ACTE developing experts by exceptionally experienced professionals& 100 % quality affirmation in preparing .
  • Our course 25000+ hours all out pragmatic situations including utilized contextual analyses.
  • Job situated situations that will make you certain while you begin chipping away at specific innovation.
  • Trainer is concentrated on every understudies to get profited with the training& best equipment set-up lab with very good quality machines .
  • Trainees will get quick reaction to any preparation related questions, either specialized or something else. We exhort our students not to stand by till the following class to look for answers to any specialized issue.
  • Instructional meetings are led by continuous trainer with real-time projects.

Data Science Course Reviews

Our ACTE Hyderabad 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

ACTE is very good platform to achieve knowledge in depth and They are providing placement for getting Job my experience and i have completed Data Science course in Hyderabad and ACTE was wonderful not only in terms of understanding the technology but also provides hands on practice to work on technology practically and the faculty is Extremely good and they help students in each and every way possible


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

Why Should I Learn Data Science Course At ACTE?

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