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Data Science Certification Training in Ludhiana

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  • Beginner & Advanced level Classes.
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  • Affordable Fees with Best curriculum Designed by Industrial Data Science Certification Expert.
  • Delivered by 9+ years of Data Science Certification Certified Expert | 12402+ Students Trained & 350+ Recruiting Clients.
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14-Oct-2024
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16-Oct-2024
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08:00 AM & 10:00 AM Batches

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

19-Oct-2024
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(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session

19-Oct-2024
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(09:00 AM - 02:00 PM)

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    Hear it from our Graduate

    Have Cracked Their Dream Job in Top MNC Companies

    Learn From Experts, Practice On Projects & Get Placed in IT Company

    • 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.
    • For Corporate, we act as one stop recruiting partner.We provide right skilled candidates who are productive right from day one.
    • 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.
    • START YOUR CAREER WITH Data Science Certification COURSE THAT GETS YOU A JOB OF UPTO 5 LACS IN JUST 60 DAYS!
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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 Ludhiana?

    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 Certification Training in Ludhiana

    A Data technological know-how definition and communication are meant to help with characterizing the facts researcher process and its motivation, simply as common abilties, capabilities, training, enjoy, and obligations. This definition in all fairness unfastened on the grounds that there isn't a normalized that means of the facts researcher process, and thinking about that the right enjoy and variety of abilties is reasonably unusual to find out in a single person.

    Data Science knowledge is the workout of mining huge information devices of uncooked information, each set up and unstructured, to choose out styles and extract actionable notion from them. This is an interdisciplinary undertaking, and the rules of information Data Science knowledge encompass statistics, inference, laptop Data Science knowledge, predictive analytics, device studying the set of rules development, and a brand new generation to benefit insights from massive information. To outline information Data Science knowledge and enhance information Data Science knowledge undertaking management, begin with its life cycle. The first degree withinside the information Data Science knowledge pipeline workflow includes capture: obtaining information, every so often extracting it, and getting into it into the system. The subsequent degree is maintenance, which incorporates information warehousing, information cleansing, information processing, information staging, and information architecture.


    Additional Info

    Introduction of Data Science

    This definition may be moreover confounded through the manner that there are exceptional jobs now after which taken into consideration as some thing similar, but are regularly very specific. A element of those comprise facts investigators, facts engineers, etc. To a extra diploma towards that later.

    Here is a chart displaying a part of the everyday trains that a facts researcher may draw upon. A facts researcher's diploma of involvement and information in every often fluctuates alongside a scale going from a fledgling, to capable, and to master, withinside the excellent case.

    While those, and exceptional disciplines and problem matters (now no longer displayed here), are for the maximum element attributes of the facts researcher process, I want to recall a facts researcher's status quo being based on 4 columns. Other extra express specialised subjects may be gotten from those columns.

    Inevitable Trend?

    One of the excellent profession possibilities withinside the Learning Data Science Online Training. You might also examine Data Science with extra opportunities. With Python, R, or SQL a candidate may also examine Data Science. Since facts technological know-how is a numerous profession, there are numerous profession potentialities at the marketplace. Upon crowning glory of the facts technological know-how path, the major process profiles are as follows:-

    • Data Scientist
    • Data Analyst
    • Data Engineer

    Advantages in facts analytics:

    the cloud is being moved from Data and exam:- proper away, groups brushed off transferring their Data stockpiling to the cloud. One situation become that the cloud become meant for fee-primarily based totally motives as opposed to for memory-inquiring for investigations. That isn't in a actual feel the case any longer. With cloud innovation quicker, cleverer, and extra versatile, severa groups have moved their Data stockrooms withinside the cloud this 12 months or had been hybridized, as an instance using a cloud-primarily based totally combination and community warehouses.

    Data and research will emerge as extra simply:-

    Additional endeavors could be made to comprise Data tiers with out a hitch, giving significant presentation sheets to an organisation. Oneself help logical gadgets marketplace will likewise maintain on creating. We are simply Data amicable in our age. As groups allow representatives at diverse ranges to study and destroy down the Data from their workstations and moreover hand held devices, the Data has grow to be extra equitable. Today, endeavors make use of self-management enterprise information (BI) fashions with progresses in innovation and computing.

    More AI and ML, extra NLP automatic:-

    The association of Data and demonstrating of Data could be extra mechanized. Thus, this can activate a ways higher and extra specific discoveries. It assists groups with staying in the front of the competition while they could take in the marketplace drifts early on.

    Customer Personalization Will Confirm Driver's Seat Consumers:-

    In Data technological know-how enterprise factors are as of now being modified. In the subsequent 12 months, we are able to see extra groups zeroing in on furnishing their buyers with an exceedingly individualized involvement with the precise time in the course of a client's shopping for journey. With growing digitalization, it's miles apparent that client personalization must be remembered for a company procedure. You want to satisfy in which your clients are. To efficiently adjust your image, you want a "Customized Customer Experience Plan" in mild of Data. All matters taken into consideration, an "locked in" client is a happy consumer

    Landscape Customer Data Platform will maintain to increase:- Customer Data tiers (CDP) had been profoundly requested, given the growing digitalization that has been seen. A CDP is a thoughts boggling Data middle point, in which the entirety linked to Data meets from Data reassets to facts for clients. In dealing with a logo every client necessarily withdraws at the back of the facts. You may comply with your impressions through using the Internet or speaking with companies on exceptional at the internet and disconnected channels, like Websites, eCommerce tiers, and in-keep encounters.


    Data Scientist Role and Responsibilities:

    Data researchers paintings in detail with enterprise companions to understand their goals and determine how facts may be applied to perform the ones goals. The plan facts shows measures, makes calculations and prescient fashions to cast off the Data the enterprise needs, and assists with analyzing the Data and provide bits of information with peers. While every mission is specific, the interplay for a social occasion and breaking down Data, through and large, comply with the beneath manner:

    • Pose the proper inquiries to begin the disclosure cycle
    • Gain Data
    • Interaction and easy the facts
    • Coordinate and keep facts
    • Beginning Data exam and exploratory Data research
    • Pick as a minimum one in all likelihood version and calculations
    • Apply Data technological know-how strategies, as an instance, AI, authentic demonstrating, and automatic reasoning
    • Gauge and in addition increase results
    • Present eventual final results to companions
    • Make modifications depending on input
    • Rehash the interplay to address any other issue

    Common Data Scientist Job Titles:

    1. Business Understanding:-The facts scientist fee to the enterprise isn't that statistical modeling can be used to increase a template. A facts scientist ought to draw close the needs of the enterprise and examine them to obtain the ones goals.

    2. Passion:-Data technological know-how is each an artwork and a technological know-how. The facts scientist must have a

    top level view of ways an excellent answer seems. There are ample media answers. It calls for endurance and backbone to discover the appropriate approach to the proper issue.

    3. Curiosity:- Data technological know-how isn't a brand new field, however new discoveries are made each 12 months. Because facts scientists constantly are looking for opportunity answers to issues. This includes searching out novel and top-rated strategies of accumulating and merging facts, preprocessing and engineering capabilities, or growing fashions and growing their strolling instances through combining software program and hardware..

    4. Innovation:- Some of the fee in facts technological know-how comes from answers now no longer earlier than taken into consideration and implemented. The first-mover benefit withinside the virtual region is actual and might make a organization or destroy it off. Many new enterprise fashions rely on how properly facts and evaluation may be used to generate a brand new and specific version, consequently facts scientists can't repeat what has formerly functioned. You ought to continually hunt for the subsequent foremost element, which differentiates your provide from different merchandise currently at the marketplace.

    5. Intuition:- Although the mathsematics concerned in analytics is foundational and proven, the use of it to remedy unique enterprise issues is an artwork form, as noted above. The facts scientist ought to have the ability to distinguish remarkable from now no longer-so-remarkable analytics.


    Data Science Certifications:

    1. Certified Analytics Professional(CAP):-

    The Certified Analytics Professional is a service provider nonpartisan affirmation that affirms which you are skilled "to convert complicated facts into giant bits of information and activities," that is precisely what groups in Data researchers appearance for: an character with a comprehension of the facts can attain smart inferences and make clear the importance of those Data focuses for key companions. You must observe and satisfy express situations earlier than you are taking the CAP or the linked degree aCAP tests

    2. Data Analyst for Cloudera Certified Associate:-

    The certificates of Cloudera Certified Associate (CCA) Data Analyst indicates your ability to drag and create Cloudera CDH reviews with Impala and Hive as a SQL designer. SQL's development abilties let you make use of Data researchers from the supply to drag, version, oversee, study and paintings with the same.

    3. Data Engineering Cloudera Certified Professional (CCP):-

    As one of the maximum inquiring for and "inquiring for declarations of execution," Cloudera has a Certified Professional (CCP) Data Engineer's Certificate. The those who want you purchased CCP Data Engineer accreditation want to have huge involvement with Data engineering.

    4. Senior Data Scientist (SDS) at the American Data Science Council (DASCA):-

    The Data Science Council of America (DaSCA) Certification Senior Data Scientist (SDS) application is meant for human beings with as a minimum 5 years of exploration and exam ability. Understudy Data on facts units, accounting pages, measurable examinations, SPSS/SAS, R, quantum procedures, and object organized programming institutions have to be established.

    5. Google Professional Data Engineer Certification:-

    The GCP Certification for Google Professional Data Engineer is maximum suitable for people with a strong Data at the Google Cloud Platform and ability withinside the introduction and the executives of GCP-primarily based totally arrangements. The evaluation will examine your capacities to create, make, steady and perform AI fashions and frameworks for getting ready facts.

    IBM Data Science Professional Certificate:-

    The IBM Data Science Professional Certificates comprise Data Science Online courses, Open-Source Instruments, Data technological know-how strategies, pythons, facts units and SQL frameworks, Data research, Data perception, gadget getting ready, and final Data technological know-how capstones.


    Why must I grow to be acquainted with a path in Data technological know-how?

    Data Science getting ready dealer for brand new understudies who want to discover on the subject of Data technological know-how and want to in addition increase their expert opportunities to carry extraordinary education and ability. ACTE gives the accompanying in particular

    • Industry races aligned.
    • Online conferences assure superb involvement.
    • Expert mentors which are properly familiar with the topic.
    • A approach to contextual analyses that profoundly seems on the possible use of the principles.
    • Possibility to accomplice with an organization of specialists in Data technological know-how.
    • Guidance of profession.
    • Feasibility of mission paintings.

    Pascale of Data Scientist

    For the Data Scientist, the everyday revenue in Ludhiana. 752,656 in keeping with annum. Depending upon your skills and enjoy the revenue package deal modifications. The scope of the Data Scientist will growth immensely within side the destiny and the call for for Data Scientist goes to be robust. So examine the Data Science Online Certification Course professionally and get the desired hands-on talents to qualify your self as a Data Scientist.

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    Key Features

    ACTE Ludhiana 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 Ludhiana
    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 Ludhiana 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 Ludhiana. 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 Ludhiana from recognized IT organizations.

    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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