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Data Science Training in Jaipur

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

  • The course teaches students how to work with data from different sources, learn machine learning, and statistical analysis.
  • The next section of the article will discuss the roles and skills associated with data science. Moreover, you'll learn what it takes to customize your data according to the audience you're reaching.
  • Several methods of analyzing data will be discussed. Projects in the area of data science are executed through various planning, execution, and presentation methods. You can get started using the tools and techniques found on this page and maximize the data for your business.
  • You will develop a very comprehensive knowledge of data science from this course. This lecture focuses on a number of fields within this field, including Data Scientists, Data Engineers, and Product Analysts.
  • During this course you will learn how to gather and analyze data using tools like R, Python, and the command line. We will also discuss various other topics such as A/B testing and market analysis.
  • The event will feature a number of major technology companies this year, including Amazon, Square, Facebook, Microsoft, Google, and Airbnb.
  • There are explanations and solutions for each question in the course as well as the quizzes. The program will not only assist you in preparing for exams, but will also prove to be useful while working.
  • It might be useful to be knowledgeable about the following topics before you go to an interview.
  • A deeper understanding of the subject matter will be gained by students through this curriculum. In addition to preparing students for interviews and training them for employment, we also provide students with opportunities for employment at companies regarded as reputable.
  • 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.
  • START YOUR CAREER WITH DATA SCIENCE COURSE THAT GETS YOU A JOB OF UPTO 5 LACS IN JUST 60 DAYS!
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Course Objectives

Data scientists carefully use their skills in maths, statistics, programming, and alternative connected subjects to organize giant data sets. Data science is high in demand and explains however digital information is remodeling businesses and helping them to make chiseler and significant selections. Therefore digital data is everywhere for people that are attempting to work as data scientists.

The demand for people with these skills can still increase, and folks already in data science roles are sure to see their salaries increase within the longer term. Data scientists work on intervals in most major industries wherever growth is going on. Not simply did IBM predict the demand for data scientists would grow by 28th in 2020, however, the Bureau of Labor Statistics estimates data science within the top 20 quickest growing occupations and has projected thirty-first growth over the subsequent 10 years.

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

  • Programming Language R/ Python.
  • Data Extraction, Transformation, and Loading.
  • Data wrangle and knowledge Exploration.
  • Machine Learning And Advanced Machine Learning (Deep Learning).
AWS jobs you'll be able to get with AWS certification Operational Support Engineer:
  • Get comfy with Python.
  • Learn information analysis, manipulation, and visualization with pandas.
  • Learn machine learning with scikit-learn.
  • Understand machine learning in additional depth.
  • Keep learning and active.
  • Apache Spark.
  • BigML.
  • D3 MATLAB.
  • Excel.
  • Ggplot2.

The objective of data science is to construct the means for extracting business-focused insights from data. This needs an understanding of how value and data flow in an exceedingly business, and also the ability to use that understanding to spot business opportunities.

Is Data Science in demand?

The potential for quantum computing and data science is big within the longer term. Machine Learning might also method the info abundant quicker with its accelerated learning and advanced capabilities. supported this, the time needed for locating advanced issues is considerably reduced. The role of the info scientist is currently a buzzworthy career. It stands within the marketplace and provides opportunities for people that study data science to form valuable contributions to their firms and societies at giant.

Does Data Science require coding background?

You need to possess knowledge of various programming languages, like Python, Perl, C/C++, SQL, and Java, with Python being the foremost common cryptography language needed in data science roles. These programming languages facilitate data scientists to prepare unstructured data sets.

Who can learn the Data Science Certification Training Course?

Data science organizations have groups from different backgrounds like chemical engineering, physics, economics, statistics, mathematics, research, technology, etc.

What is the fundamental salary for Data science software?

The average data scientist's salary is ₹698,412. An entry-level data scientist can earn around ₹500,000 annually with but one year of experience. Entry-level data scientists with 1 to 4 years of expertise get about ₹610,811 per annum.

What are the advantages of learning an Data Science Certification Training Course?

  • The abundance of Positions.
  • An extremely Paid Career.
  • Data Science is flexible.
  • Data Science Makes information higher.
  • Data scientists are extremely Prestigious.
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Overview of Data Science Training in Jaipur

Learners will study all the essential principles of Data Science in these courses, including data gathering, mining and cleaning/organizing, exploration, analysis and visualisation. Courses in Data Science in Kolkata are mostly focused on machine learning, deep learning, neural networks, predictive modelling, and natural language processing. Data Science Certification programme tasks and projects will be completed before resume building begins. Interview preparation and employment expectations will be addressed through mock interviews. This programme helps individuals prepare for examinations and job interviews by increasing their level of preparedness. Finish confidence is required for participants to effectively attend and complete the interview process.

 

Additional Info

Why learn Data Science?

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

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

    On data scientists there are various definitions. A data scientist performs the art of data science in simple language. After contemplating that a data scientist pulls a great deal of knowledge from science areas and applications, whether it be statistics or mathematics, the name "data scientist' was coined.

    What is a scientist doing?

    In various scientific areas, data scientists are individuals who are cracking difficult data issues. They work with various components in mathematics, statistics, informatics, etc (though they may not be an expert in all these fields). They employ state-of-the-art technology to identify answers and to draw conclusions which are important to the growth and development of an organisation. In comparison with the raw data available from structured and unstructured formats, data scientists provide the data in a far more usable way. You may read this article on Who is a data scientist to learn more aboutIntelligence Business (BI) vs. Data Science Company Intelligence (BI) examines the past data in order to obtain a retrospect and an insight into business patterns. In this section, BI allows you to capture, prepare and query data from internal and external sources and to construct dashboards that answer questions such as a quarterly revenue analysis or business issues. In the near future, BI can assess the influence of such occurrences.

    Data Science Lifecycle:

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

    Phase 1 — Discovery:- it is essential to grasp the different specifications, needs, priorities and budgets necessary before beginning the project. You need to be able to ask the correct questions. Here, you evaluate if you have the resources necessary to support the project, including people, technology, time and data. At this stage the business challenge has to be framed and initial hypotheses (IH) formulated to be tested.

    Phase 2—Processing of data:- In this phase, you need an analytical sandbox in which you may analyse the whole project. Before modelling, you need to examine, pre-process and condition data. In order to obtain your data in the sandbox, you will also execute ETLT (extract, transform, load and transform). Let's look at the following flow of statistical analysis. You may use R to purify, process and view data. This helps you to identify the outliers of the variables and to create a connection. It is time to perform exploration analysis once you have cleaned and prepped the data. Let's see how it is possible.

    Phase 3 - Model Planning:- Model Data Science - Edureka Here the strategies and approaches for drawing links between variables are defined. These connections provide the basis for the algorithms that you are using in the following stage. You use numerous statistical formulae and visualisation tools to implement Exploratory Data Analytics (EDA).

    Phase 4 — Model construction:- You will generate data sets for training purposes and testing reasons in this phase. Here is if your present tools are sufficient to run the models or a more robust environment is needed (like fast and parallel processing). To create the model, you will study several learning approaches such as grading, association and grouping.

    Phase 5—Operationalizing:- Operationalizing data science - Edureka You submit final reports, briefings, code and technical documentation in this phase. Furthermore, a pilot project is occasionally executed in a production environment in real-time. This gives you a good view before complete deployment of your performance and other associated restrictions on a small scale.

    Phase 6—Transmit results:- Now it is vital to assess if you have achieved your aim in the first phase. So in the last stage, all of the important findings are identified, the stakeholders are communicated and whether the project outcomes are successful or a failure based on the criteria.

    Certification course on data science:

    Data science is a "concept for the unification of statistics and analyses of data and their corresponding techniques" to "understand and analyse real events" with data. In the realms of mathematics, statistics, information science and computer sciences the Data Science education uses the techniques and ideas from various subjects from machine learning, classification, cluster analytics, information mining, databases and viewing. The Data Science certification course enables you to get an overview of the data science life cycle, analysis and view various data sets, various machine learning algorithms such as K-Means clustering, decision-making.

    What are the goals of our online course in data sciences?

    The training in data sciences is meant to make you a Certified Data Scientist by industrial professionals. The Courses in Data Science:

  • Data Science Life Cycle knowledge and Algorithms for Machine Learning
  • Extensive understanding of several data transformation tools and methodologies
  • the capacity to do text and sentimental data analysis and to obtain an overview of data visualisation and optimisation approaches
  • The exhibition of numerous industrial real-life projects in RStudio
  • Diverse projects in the fields of media, health, social media, aviation and human resources
  • Strong participation by a SME in the data science training to understand industry standards and best practises
  • Why do you want to train in data science?

    In cross-disciplinary disciplines such as business analysis that combine IT science, modelling, statistics and analytics, data science is the evolutionary step. You need structured training with an updated curriculum according to current industry needs and best practises to take full advantage of these prospects. In order to get a data set, processing, and inspiration from the data set, extract relevant data from the set, and interpret it for decisions, you must work on a number of real-life projects utilising several tools in many disciplines. You need the guidance, moreover of an expert who works in the industry to address the real issues of data.

    What skills will you acquire from our Data Science Training?

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

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

    The Data Analytics industry is developing worldwide, and this strong trend of growth offers all IT professionals an excellent chance. Our data science training lets you seize this chance and speed up your career through the application of data approaches on many types. For: developers that aspire to be a "data scientist"

  • Managers of analytics who head a team of analysts
  • Analysts wishing to grasp the techniques of machine learning (ML)
  • Architects of information who would like skills in predictive analysis
  • Professionals that want to work with big data
  • Analysts who wish to know Data science methodologies
  • The Data Science job profiles include:

    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. On the other side, the data engineer develops, maintains and supports scalable data pipelines and builds APIs to the data repositories. In data formats and big data technol, data models have become diversified in type and expertise.

    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.

    Advantages of Data Science

    The various benefits of Data Science are as follows:

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

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

    3. A Highly Paid Career:- Data Science is one of the most highly paid jobs. According to Glassdoor, Data Scientists make an average of $116,100 per year. This makes Data Science a highly lucrative career option.

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

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

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

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

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

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

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

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    Key Features

    ACTE Jaipur 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.
     

    Curriculum

    Syllabus of Data Science Course in Jaipur
    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
    Air Pollution Prediction project

    The objective of ambient air sampling is determining the quality of ambient air as it relates to the presence and concentration of substances regarded as pollutants.

    Project 2
    Age and Gender Detection Project

    The objectives of the project are mainly to detect faces, classify into male/female, classify into one of the 8 age ranges then put the results in image and then display it.

    Project 3
    Optimizing Product Price Project

    price optimization uses data analysis techniques to pursue two main objectives Understanding how customers will react to different pricing strategies for products and services.

    Project 4
    IMDB Predictions Project

    Our object is to build a system to predict IMDB users' rating about movies with different algorithms and compare their performance through a benchmark.

    Our Engaging Placement Partners

    ACTE Jaipur offers arrangement openings as extra to each understudy/proficient who finished our study hall or internet preparing. A portion of our understudies are working in these organizations recorded underneath.
    • ACTE putting together delicate abilities preparing to improve the understudy's character, certainty level, public talking abilities, leading fake meetings, gathering conversations.
    • We provide the applicants to confront the difficulties of the determination cycle by directing intermittent general fitness tests, specialized inclination tests, bunch conversations, mock meetings and so forth, and making them for the most part mindful of the modern situation and so on.
    • Regular collaboration by the situation official with the understudies for tweaking and sorting out the meetings for making the understudies employable and to meet the corporate assumptions.
    • Organizing business venture advancement projects to spur the Understudies to become Business visionaries.
    • Our placement cell works with delicate expertise preparing programs, courses, industry-establishment communications, workshops, inclination tests, direction and advising classes, cutthroat test trainings and getting situations for understudies in presumed associations. The preparation and arrangement cell gives direction and help to empower the understudies gain the most ideal employability and business venture abilities. It's anything but a stage to get to and assimilate significant assets and furthermore goes about as an interface with different organizations who are looking for skilled understudies in different controls.
    • After fulfillment of 70% Data Science Training in Jaipur Course content, we will mastermind the meeting calls to understudies and set them up to F2F collaboration.

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

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

    Complete Your Course

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

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

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    About Qualified Data Science Mentor

    • Our Data Science Training in Jaipur. Trainers fostering the understudy's specialized information and delicate abilities to meet the corporate enlistment measure.
    • Trainers furnishes Learners with long lasting, profession dynamic skills& likewise Giving assets and exercises to work with the vocation arranging measure.
    • Tutors masterminding professional preparing to understudies in appropriate businesses relying upon their aptitudes and abilities.
    • Lectures provide the divisions in orchestrating project works for applicants in rumored businesses with the goal that the understudies get involved involvement with taking care of modern issues.
    • Trainer guarantees appropriate and opportune contributions on human asset prerequisites through contact from the mechanical accomplices. the group plans far reaching preparing programs, which isn't limited to however is comprehensive of specialized, social, programming, establishment in arithmetic, Sensible and insightful Preparing, and a lot more customized preparing programs for the all encompassing advancement of an applicants.
    • To match the business needs and models of our up-and-comers, our coaches have made an all around Data Science Training class. also, We have gotten a couple of huge distinctions for Data Science Training in Jaipur from remarkable IT associations .

    Data Science Course Reviews

    Our ACTE Jaipur 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.

    Nandhini

    Student

    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.

    Pavith

    Software Engineer

    I have completed my Data Science course from REAL TIME EXPERT. My trainer was very good his teaching was very good. I got good practical classes also. I strongly recommend for best classes in ACTE. I have seen lot of real time trainers working in Jaipur.

    Ebenazar

    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.

    Illakiya

    Student

    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.

    Tharani

    Software Engineer

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

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    Data Science Course FAQs

    Looking for better Discount Price?

    Call now: +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 ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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    Request for Class Room & Online Training Quotation

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