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Data Science Training in Patna

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  • We train students for interviews and Offer Placements in corporate companies.
  • Ideal for graduates with 0 – 3 years of experience & degrees in B. Tech, B.E and B.Sc. IT Or Any Computer Relevent.
  • You will not only gain knowledge of Data Science Certification and Advance tools, but also gain exposure to Industry best practices, Aptitude & SoftSkills.
  • Experienced Trainers and Lab Facility.
  • IBM Data Science Certification Professional Certificate Guidance Support with Exam Dumps.
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  • Resume & Interviews Preparation Support.
  • Concepts: Data Science Certification , significance of Data Science Certification in today’s digitally-driven world, components of the Data Science Certification 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

The potential for quantum computing and data science is big within the future. Machine Learning may also method the data abundant quicker with its accelerated learning and advanced capabilities. supported this, the time needed for finding advanced issues is considerably reduced. The role of the data scientist is currently a buzzworthy career. It's standing within the marketplace and provides opportunities for folks that study data science to create valuable contributions to their firms and societies at giant.

Big data. Data scientists shrewdness to use their skills in maths, statistics, programming, and alternative connected subjects to prepare giant information sets. Then, they apply their knowledge to uncover solutions hidden within the information require on business challenges and goals. Data science is high in demand and explains however digital information is remodeling businesses and serving to them create chiseler and significant selections. therefore digital data is everywhere for folks that are trying to figure as a data scientist.

  • 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
With the correct qualifications, you’ll get pleasure from a bright career outlook as a knowledgeable soul. The demand for people with these skills can still increase, and people already in data science roles are bound to see their salaries increase within the future. Data scientists work at intervals in most major industries wherever growth is occurring. Not only did IBM predict the demand for data scientists would grow by 28th in 2020, however, the Bureau of Labor Statistics considers data science within the prime twenty quickest growing occupations and has projected thirty-first growth over the following 10 years.
Data science groups have folks from various backgrounds like chemical engineering, physics, economics, statistics, mathematics, research, technology, etc. You'll realize several data scientists with a bachelor's degree in statistics and machine learning however it's not a demand to be told Data Science.
The various edges of Data Science are as follows:
  • The abundance of Positions
  • An extremely Paid Career
  • Data Science is flexible
  • Data Science Makes information higher
  • Data scientists are extremely Prestigious
  • Apache Spark
  • BigML
  • D3 MATLAB
  • Excel
  • ggplot2

What are the purposes of the Data Science Certification?

The key objective of Data Science is to extract valuable data to be used in the strategic higher cognitive process, development, analytic thinking, and statement. The key techniques in use are data processing, huge data analysis, data extraction, and data retrieval. The purpose of data science is to create the means for extracting business-focused penetrations from data. This requires an understanding of however worth and data flows in an extremely business, and therefore the ability to use that understanding to find business opportunities.

What skills are utilized in a Data Science Online Training in Patna?

One of the foremost necessary technical knowledge soul skills is applied math analysis and computing, mining, and process big data sets. This additionally includes extracting the info that's thought valuable. Some information scientists have a pH scale
  • Statistics
  • Programming Language R/ Python
  • Data Extraction, Transformation, and Loading
  • Data wrangle and information Exploration
  • Machine Learning And Advanced Machine Learning (Deep Learning)

What are the job opportunities after completing the Data Science Certification Course?

To name many, a number of the foremost common job titles for information scientists include:
  • Business analyst
  • Data Mining Engineer
  • Data designer
  • Data Scientist
  • Senior Data Scientist

What are the requirements for learning Data Science Certification?

Data science requires the basics of statistics and mathematics, which should be clear to be able to analyze the problems that are at hand. To solve business problems, you need to have soft skills like team management and control over the projects to meet the deadlines. You will find many data scientists with a bachelor's degree in statistics and machine learning but it is not a requirement to learn data science

Will Data Science requires coding background?

You need to possess knowledge of different 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 organize unstructured data sets.6
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Overview of Data Science Course in Patna

Data Science understanding is the exercising of mining massive records gadgets of raw records, every installed and unstructured, to select out patterns and extract actionable belief from them. This is an interdisciplinary challenge, and the regulations of records Data Science understanding include statistics, inference, pc Data Science understanding, predictive analytics, tool mastering the set of regulations development, and a new era to advantage insights from big records. To define records Data Science understanding and decorate records Data Science understanding challenge management, start with its existence cycle. The first diploma withinside the records Data Science understanding pipeline workflow consists of capture: acquiring records, once in a while extracting it, and entering into it into the system. The next diploma is maintenance, which includes records warehousing, records cleansing, records processing, records staging, and records architecture.


Additional Info

Introduction of Data Science Certification Course :

Data processing follows and constitutes one of the records of Data Science understanding fundamentals. It is for the duration of records exploration and processing that records scientists stand aside from records engineers. This diploma consists of records mining, records elegance and clustering, records modeling, and summarizing insights gleaned from the records—the techniques that create effective records. Next comes records assessment, and in addition essential diploma.

Roles of Data Science Online Training :

    Data Science is characterized by the useful resource of the usage of its variety and amount, every of this is essential for Data Science. Data Science captures the complex patterns from Data Science with the useful resource of the usage of developing Machine Learning Models and Algorithms. Data Science is that this sort of challenge that can be carried out in almost every agency to remedy complex problems. Every agency applies Data Science to a one-of-a-type application with the view of solving a one-of-a-type problem. Some groups depend upon Data Science and Machine Learning techniques to remedy a high-quality set of problems, which, otherwise, could not be solved. Some of such applications of Data Science and the groups withinside the returned of them are listed below.

  • Internet Search Results (Google):
  • When someone searches for something on Google, complex Machine Learning algorithms determine which can be the most relevant results for the search length (s). These algorithms help to rank pages such that the most relevant records are furnished to the character on the urgent of a button.

  • Recommendation Engine (Spotify):
  • Spotify is a music streaming provider that is quite well-known for its cappotential to advocate music in line with the taste of the character. This is an exquisite example of Data Science at play. Spotify’s algorithms use the records generated with the useful resource of the usage of all people over the years to observe the character’s taste in music and advocate him/her with similar music withinside the future. This shall we the agency draw extra clients on account that it's far extra available for the character to use Spotify as it does now not name for an entire lot of attention.

  • Intelligent Digital Assistants (Google Assistant):
  • Google Assistant, much like exclusive voice or text-based digital assistants (moreover referred to as chatbots) is one example of advanced Machine Learning algorithms located to use. These algorithms can convert the speech of someone (no matter one-of-a-type accents and languages) to text, apprehend the context of the text/command, and provide relevant records or perform a desired task, all surely with the useful resource of the usage of speaking to the tool.

  • Spam Filter (Gmail):
  • Another key application of Data Science which we use in our everyday existence is the direct mail filters in our emails. These filters mechanically separate the direct mail emails from the rest, correctly giving the character a far cleanser e-mail enjoy. Just much like the exclusive applications, Data Science is the critical component building block here.

  • Abusive Content and Hate Speech Filter (Facebook):
  • Similar to the junk mail filter, Facebook and different social media systems use Data Science and Machine Learning algorithms to clear out abusive and age-confined content material from the accidental audience.

  • Robotics (Boston Dynamics):
  • Similar to the direct mail filter, Facebook and exclusive social media structures use Data Science and Machine Learning algorithms to clean out an abusive and age-restrained content material cloth from the unintended audience.

  • Automatic Piracy Detection (YouTube):
  • Most films that are probably uploaded to YouTube are real content material cloth created with the useful resource of the usage of content material cloth creators. However, quite regularly, pirated and copied films are also uploaded to YouTube, that is their policy. Due to the sheer amount of regular uploads, it is not possible to manually come across and takedown such pirated films. This is in which Data Science is used to mechanically come across pirated films and remove them from the platform.


What is Data Science?

Data Science is a multidisciplinary challenge that uses medical inference and mathematical algorithms to extract huge information and insights from a massive amount of installed and unstructured records. These algorithms are implemented through pc applications which can be usually run on powerful hardware as it requires a massive amount of processing. Data Science is a combination of statistical mathematics, tool mastering, records assessment and visualization, location information, and pc Data Science understanding. As it's far apparent from the call, the most essential detail of Data Science is “Data” itself. No amount of algorithmic computation can draw huge insights from wrong records. Data Data Science understanding consists of numerous varieties of records, for example, photograph records, text records, video records, time-primarily based records, etc. Our Data Science Training in Patna is well-ready with labs and exquisite infrastructure to offer you hands-on training. In addition, we offer Data Science certification training.

Trends Of Data Data Science:

    The challenge of Data Science has been growing ever on account that its onset withinside the period. With time, the increasing current era is being incorporated into the challenge. Some of such extra ultra-modern additions are listed below:

  • Artificial Intelligence:
  • Machine Learning has been one of the significant elements of Data Science. However, with the accelerated parallel compute capabilities, Deep Learning has been the modern and one of the most massive additions to the Data Science challenge.

  • Edge Computing:
  • Edge computing is in recent times developed concept and is related to IoT (Internet of Things). Edge computing locations the Data Science pipeline of records collection, delivery, and processing withinside the course of the delivery of records. This is possible through IoT and has in recent times been delivered to be a part of Data Science.

  • Security:
  • Security has been a major undertaking withinside the digital space. Malware injection and the concept of hacking are quite now no longer unusualplace and all digital systems are vulnerable to it. Fortunately, there have been few ultra-modern Data Science upgrades that exercise Data Science techniques to prevent the exploitation of digital systems. For example, Machine Learning techniques have verified the extra capability of detecting pc viruses or malware while in evaluation to traditional algorithms.


What is the motive of facts Data Science ?

The primary cause of Data Science is to find out patterns in interior records. It uses numerous statistical techniques to analyze and draw insights from the records. From records extraction, wrangling, and pre-processing, a Data Scientist needs to scrutinize the records thoroughly.

Skills required to grow to be a Data Scientist:

    As stated withinside the previous section, Data Science is a complex challenge. Hence, it requires the mastery of multiple sub-fields, which together add as a good deal because the whole information required to be a Data Scientist.

    1. Mathematics:

    The first and the most essential challenge of commentary to turn out to be a Data Scientist is mathematics; extra especially, Probability and Statistics, Linear Algebra, and some number one Calculus.

  • Statistics:
  • It is essential in EDA and developing algorithms to conduct statistical inference on the records. Additionally, most Machine Learning Algorithms use statistics as their vital building blocks.

  • Linear Algebra:
  • Working with a big variety of records method jogging with high-dimensional matrices and matrix operations. The records that the model takes in and the handiest that it gives as output are withinside the form of matrices and therefore any operation that is done on them uses the fundamentals of Linear Algebra.

  • Calculus:
  • Since Data Science does include Deep Learning, calculus is of massive importance. In Deep Learning, calculation of Gradient can be very essential and is performed at every step of computation in Neural Networks. This requires legitimate information on differential and vital calculus.

2. Algorithmic Knowledge:

Even even though Data Science normally does now not consists of the development and format of Algorithms like a few different applications of Computer Science does, it's far even though essential for a Data Scientist to have valid information of Algorithms. This is because of the reality, on the forestall of the day, Data Scientists are programmers who are expected to expand applications that could derive huge insights from records. Having algorithmic information shall we the Data Scientist write down huge inexperienced code, which saves on every occasion and supply and therefore is rather valued.

3. Programming Languages (R and Python):

Even even though any programming language can be used for any form of logical use case, which of course, includes Data Science; but, the most generally used languages are R and Python. Both of these languages are open deliver and therefore have big community support, have multiple libraries developed preserving Data Science in mind, and are mainly smooth to observe and use. Without the information of programming languages, a Data Scientist cannot exercise any form of algorithmic or mathematical information of the records.

4. Proper Programming Environment:

Since sound programming information is one of the key requirements for Data Science, there desires to be an available platform to jot down and execute the code. This platform is referred to as the IDE or Integrated Development Environment. There are severa IDEs to select out from, and some of them have been mainly developed for Data Science. This article talks about the Top 10 Python IDEs.

5. SQL:

Databases are of massive importance withinside the challenge of Data Science on account that they may be the most suitable method to storing records. Thorough information of one or extra database era like MySQL, MariaDB, PostgreSQL, MS SQL Server, MongoDB, Oracle NoSQL, etc.

6. Machine Learning Frameworks:

Machine Learning is an essential part of Data Science and its implementation consists of high-quality libraries and frameworks, the information of which can be essential for any Data Scientist. Here, some of the most generally used Machine Learning frameworks are listed.

  • Numpy:
  • This is a library that allows the smooth implementation of linear algebra and records manipulation.

  • Pandas:
  • This library is used to load, adjust and maintain records. This is also applied in records wrangling.

  • Matplotlib:
  • This is one of the most generally used libraries for records visualization.

  • Seaborn:
  • This is a wrapper over Matplotlib, that is used to visualize extra complex records.

  • Sklearn:
  • This is used to apply and positioned into impact most of the tool mastering algorithms and records preprocessing techniques.

  • Tensorflow:
  • This is a deep getting-to-understand framework backed with the useful resource of the usage of Google and allows smooth implementation of numerous varieties of neural networks.

  • PyTorch:
  • Similar to TensorFlow, that is moreover a deep mastering framework that is regularly used.

  • Keras:
  • This is a wrapper that works together with TensorFlow and allows mainly smooth implementation of Deep Learning techniques.

  • OpenCV:
  • This is a pc vision framework and is usually used for Image Processing and photo manipulation.


    Future of Data Science Certification Training :

    Data Science is an ever-growing challenge and is expected to increase in a name for withinside the foreseeable future. Some of the critical component changes are listed below.

    Data: With the radical increase of the technology of records, the general overall performance of the predictive algorithms is going to decorate over the years as extra records are available to draw inference upon. This phenomenon is fueled with the useful resource of the usage of the growth of Social Media and IoT-based devices, which generate masses extra records.

    Algorithms: Machine Learning algorithms like Genetic Algorithms and Reinforcement Learning algorithms are expected to decorate over the years causing extra clever systems.

    Distributed Computing: With the upgrades of the blockchain era, TPU (Tensor Processing Unit) development, and faster GPU (Graphics Processing Unit) available withinside the cloud, Data Science sees a future in which extra powerful computational hardware aids the algorithms of developing complexity.

    Career Growth of Data Science Certification Training in Patna :

    The 21 century will be ruled with the useful resource of the usage of records. Data Science has grown to be an essential part of many corporations and industries. It affords precious insights into customer behavior which can bring about accelerated conversions, extra genuine market assessment for competitive advantage in pricing strategies or product development, stepped forward operational efficiency, and minimized chance exposure through accurate forecasting models.

    Advantages Of Data Science Certification Training :

    1. Increases commercial enterprise predictability

    Increases business agency predictability is an agency invests in structuring its records, it can work with what we call predictive assessment. With the help of the records scientists, it's far possible to use era collectively with Machine Learning and Artificial Intelligence to Work with the records that the agency has and, in this manner, carry out extra unique analyses of what is to come. Thus, you increase the predictability of the industrial agency and can make picks in recent times in a manner to affect the future of your business agency.

    2. Ensures real-time intelligence

    Ensures real-time intelligence records of scientists can Work with RPA professionals to select out the property of the one-of-a-type records of their business agency and create automated dashboards, which are trying to find most of these records in real-time in an included manner. This intelligence is essential for the managers of your agency to make extra accurate and faster picks.

    3. Favors the advertising and income place

    Favors the marketing and marketing and profits location data-driven Marketing is a famous length in recent times. The cause is simple: simplest with records, we can offer solutions, communications, and products that are probably actually consistent with customer expectations. As we have got seen, records scientists can integrate records from certainly considered one among the sort property, bringing even extra accurate insights to their team. This is possible with Data Science.

    4. Improves facts security

    Improves records securityOne of the benefits of Data Science is the Work is performed withinside the location of ​​records security. In that sense, there can be a global of possibilities. The records scientists Work on fraud prevention systems, for example, to hold your agency’s customers safer. On the opportunity hand, he can also study everyday types of behavior in an agency’s systems to select out out possible architectural flaws.

    5. Helps interpret complicated facts

    Helps interpret complex records data Science is a superb solution while we want to transport one-of-a-type records to apprehend the industrial agency and the market better. Depending on the equipment we use to build up records, we can combo records from “physical” and virtual property for better visualization.

    6. Facilitates the decision-making process

    Facilitates the selection-making process of course, from what we have got exposed so far, you need to already trust that one of the benefits of Data Science is improving the selection-making process. This is because of the reality we can create equipment to view records in real-time, allowing extra agility for business agency managers. This is performed every with the useful resource of the usage of dashboards and with the useful resource of the usage of the projections which is probably possible with the records scientist’s treatment of records.

    Salaries of a Data Scientist In Patna:

    The Data Science challenge is one of the most paying jobs withinside the software program application location. It is also the satisfactory paying with the lowest amount of relevant Work enjoy while in evaluation to a few different challenges withinside the software program application location, as verified withinside the parent.

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    Key Features

    ACTE Patna offers Data Science Certification 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 Certification Training in Patna
    Module 1: Introduction to Data Science Certification with R
    • What is Data Science Certification , significance of Data Science Certification in today’s digitally-driven world, applications of Data Science Certification , lifecycle of Data Science Certification , components of the Data Science Certification 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 Certification Projects

    Project 1
    Wallmart Sales Data Set

    Retail is another industry that extensively uses analytics to optimize business processes.

    Project 2
    Flipkart Classification Dataset

    This project is to forecast sales for each department and increasing labelled dataset using semi-supervised classification.

    Our Top Hiring Partner for Placements

    ACTE Patna offers placement opportunities as add-on to every student / professional who completed our classroom or online training. Some of our students are working in these companies listed below.
    • We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
    • We have separate student’s portals for placement, here you will get all the interview schedules and we notify you through Emails.
    • After completion of 70% Data Science Certification training course content, we will arrange the interview calls to students & prepare them to F2F interaction
    • Data Science Certification Trainers assist students in developing their resume matching the current industry needs
    • We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
    • We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge

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

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

    Complete Your Course

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

    Get Certified

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

    Get Certified

    About Experienced Data Science Certification Trainer

    • Our Data Science Certification Training in Patna. Trainers are certified professionals with 7+ years of experience in their respective domain as well as they are currently working with Top MNCs.
    • As all Trainers are Data Science Certification domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
    • All our Trainers are working with companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc.
    • Trainers are also help candidates to get placed in their respective company by Employee Referral / Internal Hiring process.
    • Our trainers are industry-experts and subject specialists who have mastered on running applications providing Best Data Science Certification training to the students.
    • We have received various prestigious awards for Data Science Certification Training in Patna from recognized IT organizations.

    Data Science Certification Course Reviews

    Our ACTE Patna 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.

    Sureli

    Software Engineer

    Data Science class was really helpful in building my career. They cleared my basic concepts and helped me practice for the interviews. They made sure that I understood all the basics and prepared me for the industry. I am thankful for ACTE the staff for their efforts and determination.

    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 Certification 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 Certification 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 Certification Course At ACTE?

    • Data Science Certification Course in ACTE is designed & conducted by Data Science Certification experts with 10+ years of experience in the Data Science Certification 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 Certification batch to 5 or 6 members
    Our courseware is designed to give a hands-on approach to the students in Data Science Certification . 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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