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Data Science Certification Training in Ankara

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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.
  • 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.
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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
  • 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 Ankara?

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 Ankara

Data science is the field of study that joins space mastery, programming abilities, and data on math and measurements to remove significant experiences from the information. Information science experts apply AI calculations to numbers, text, pictures, video, sound, and more to deliver AI frameworks to perform undertakings that usually require human knowledge. Thusly, these frameworks create bits of knowledge that examiners and business clients can convert into substantial business esteem.

A Data science definition and conversation are intended to assist with characterizing the data researcher job and its motivation, just as average abilities, capabilities, schooling, experience, and obligations. This definition is fairly free since there is not a normalized meaning of the data researcher job, and considering that the ideal experience and range of abilities is moderately uncommon to discover in one person.


Additional Info

About Data Science

Data science is the study of extracting useful insights from data by combining subject experience, computer abilities, and understanding of mathematics and statistics. Data scientists apply machine learning algorithms to numbers, text, photos, video, and audio, among other things, to create artificial intelligence (AI) systems that can execute jobs that would normally need human intelligence. As a result, these systems generate insights that analysts and business users can employ to create meaningful commercial value.

This definition can be additionally confounded by the way that there are different jobs now and then considered as something similar, yet are frequently very unique. A portion of these incorporate data investigators, data engineers, etc. To a greater degree toward that later.

A data researcher's degree of involvement and knowledge in each regularly fluctuates along a scale going from a fledgling, to capable, and to master, in the best case.

While these, and different disciplines and subject matters (not displayed here), are for the most part attributes of the data researcher job, I like to consider a data researcher's establishment being founded on four columns. Other more explicit specialized topics can be gotten from these columns.

Data Science Certifications:

Certified Analytics Professional(CAP):- The Certified Analytics Professional is a merchant nonpartisan confirmation that affirms that you are skilled "to transform complex data into significant bits of knowledge and activities," which is exactly what organizations in Data researchers look for: an individual with a comprehension of the data can reach intelligent inferences and clarify the significance of these Data focuses for key partners. You should apply and fulfill explicit conditions before you take the CAP or the connected level aCAP tests

Data Analyst for Cloudera Certified Associate:- The certificate of Cloudera Certified Associate (CCA) Data Analyst shows your capacity to pull and create Cloudera CDH reports with Impala and Hive as a SQL designer. SQL's advancement abilities permit you to utilize Data researchers from the source to pull, model, oversee, examine and work with the same.

Data Engineering Cloudera Certified Professional (CCP):- As one of the most requesting and "requesting declarations of execution," Cloudera has a Certified Professional (CCP) Data Engineer's Certificate. The people who need to procure CCP Data Engineer accreditation need to have broad involvement with Data engineering.

Senior Data Scientist (SDS) on the American Data Science Council (DASCA):- The Data Science Council of America (DaSCA) Certification Senior Data Scientist (SDS) program is intended for people with at least five years of exploration and examination ability. Understudy Data on data sets, accounting pages, measurable examinations, SPSS/SAS, R, quantum procedures, and item arranged programming establishments ought to be established.

Google Professional Data Engineer Certification:- The GCP Certification for Google Professional Data Engineer is most appropriate for individuals with a solid Data on the Google Cloud Platform and skill in the creation and the executives of GCP-based arrangements. The assessment will assess your capacities to create, make, secure and carry out AI models and frameworks for preparing data.

IBM Data Science Professional Certificate:- The IBM Data Science Professional Certificates incorporate Data Science Online courses, Open-Source Instruments, Data science strategies, pythons, data sets and SQL frameworks, Data investigation, Data perception, machine preparing, and last Data science capstones.

Why should I become familiar with a course in Data science?

ACTE is a Data Science preparing supplier for new understudies who need to find out with regards to Data science and need to further develop their professional possibilities to convey incredible preparation and ability. ACTE offers the accompanying in particular;

  • Industry races aligned.
  • Online meetings guarantee magnificent involvement.
  • Expert mentors that are well acquainted with the topic.
  • A technique to contextual analyses that profoundly looks at the viable use of the principles.
  • Possibility to associate with an organization of experts in Data science.
  • Guidance of career.
  • Feasibility of venture work.

Data Scientist Role and Responsibilities

Data Scientist

Data researchers look at which questions need addressing and where to track down the connected information. They have business keenness and logical abilities just as the capacity to mine, clean, and present information. Organizations use information researchers to source, oversee, and break down a lot of unstructured information. Results are then orchestrated and conveyed to key partners to drive vital dynamics in the association.

Abilities required: Programming abilities (SAS, R, Python), measurable and numerical abilities, narrating and information representation, Hadoop, SQL, AI.

Data Analyst

Data experts overcome any issues between information researchers and business investigators. They are furnished with the inquiries that need responding to from an association and afterward arrange and investigate information to discover results that line up with significant level business technique. Data examiners are answerable for making an interpretation of specialized investigation to subjective things to do and successfully imparting their discoveries to different partners.

Abilities required: Programming abilities (SAS, R, Python), factual and numerical abilities, information fighting, information representation.

Data Engineer

Information engineers oversee dramatic measures of quickly evolving information. They center around the turn of events, organization, the executives, and streamlining of information pipelines and framework to change and move information to information researchers for questioning.

Abilities required: Programming dialects (Java, Scala), NoSQL information bases (MongoDB, Cassandra DB), systems (Apache Hadoop).

Data analysts work personally with colleagues to understand their targets and choose how information can be used to achieve those goals. The arrangement information shows measures, makes estimations and judicious models to eliminate the Data the business needs, and helps with analyzing the Data and deal pieces of information with peers. While each adventure is extraordinary, the communication for a get-together and separating Data, all things considered, follow the under way:

  • Pose the right inquiries to start the disclosure cycle
  • Gain Data
  • Interaction and clean the data
  • Coordinate and store data
  • Beginning Data examination and exploratory Data investigation
  • Pick at least one likely model and calculations
  • Apply Data science strategies, for example, AI, factual demonstrating, and computerized reasoning
  • Gauge and further develop results
  • Present eventual outcome to partners
  • Make changes dependent on input
  • Rehash the interaction to tackle another issue
  • Common Data Scientist Job Titles:

    The most widely recognized vocations in Data science incorporate the accompanying jobs.

    Data researchers: Design Data demonstrating cycles to make calculations and prescient models and perform custom investigation.

    Data experts: Manipulate enormous Dataal collections and use them to distinguish patterns and arrive at significant resolutions to advise key business choices.

    Data engineers: Clean, total, and put together Data from dissimilar sources and move it to Data stockrooms.

    Five features of a Business Understanding Scientist:

    1. Business Understanding:- The data scientist value to the company is not that statistical modeling may be used to develop a template. A data scientist must grasp the demands of the company and analyze them to achieve those goals.

    2. Passion:- Data science is both an art and a science. The data scientist should have an overview of how a good solution looks. There are abundant media solutions. It requires patience and determination to find the perfect solution to the right issue.

    3. Curiosity:- Data science is not a new field, but new discoveries are made every year. Because data scientists continuously seek alternative solutions to issues. This involves looking for novel and optimal techniques of gathering and merging data, preprocessing and engineering features, or developing models and increasing their running times by combining software and hardware.

    4. Innovation:- Some of the value in data science comes from solutions not before considered and implemented. The first-mover advantage in the digital sector is true and can make a firm or break it off. Many new business models depend on how well data and analysis can be used to generate a new and unique model, therefore data scientists cannot repeat what has previously functioned. You must always hunt for the next major element, which differentiates your offer from other products presently on the market.

    5. Intuition:- Although the math involved in analytics is foundational and proven, using it to solve specific business problems is an art form, as mentioned above. The data scientist must be able to differentiate great from not-so-great analytics.

    Why Data Science is Important?

    An ever-increasing number of organizations are coming to understand the significance of information science, AI, and AI. Notwithstanding industry or size, associations that wish to stay serious in the time of huge information need to effectively create and execute information science capacities or hazard being abandoned.

    What Does a Data Scientist Do?

    In the previous decade, data researchers have become essential resources and are available in practically all associations. These experts are balanced, information-driven people with undeniable level specialized abilities who are equipped for building complex quantitative calculations to coordinate and orchestrate a lot of data used to address questions and drive methodology in their association. This is combined with the involvement with correspondence and authority expected to convey unmistakable outcomes to different partners across an association or business.

    Data researchers should be interested and result-arranged, with uncommon industry-explicit data and relational abilities that permit them to disclose exceptionally specialized outcomes to their non-specialized partners. They have a solid quantitative foundation in measurements and straight polynomial math just as programming information with centers in information warehousing, mining, and demonstrating to assemble and break down calculations.

    Future Trend?

    One of the best career opportunities in the Learning Data Science Online Training. You may also learn Data Science with additional possibilities. With Python, R, or SQL a candidate may learn Data Science. Since data science is a diverse profession, there are several career prospects on the market. Upon completion of the data science course, the predominant job profiles are as follows:-

    Best Job in Ankara in 2018 for the third year straight. As expanding measures of information become more available, enormous tech organizations are as of now not the only ones needing information researchers. The developing interest for information science experts across enterprises, of all shapes and sizes, is being tested by a deficiency of qualified competitors accessible to fill the open positions.

    The requirement for information researchers does not indicate dialing back in the coming years. The most encouraging job in 2017 and 2018, alongside numerous information science-related abilities as the most sought after by organizations. The measurements recorded below address the huge and developing interest for information researchers.

    • Data Scientist
    • Data Analyst
    • Data Engineer

    Advantages in information analytics:

    Yes, the cloud is being moved from Data and assessment:- immediately, associations excused moving their Data accumulating to the cloud. One concern was that the cloud was expected for esteem based reasons rather than for memory-mentioning examinations. That isn't from a genuine perspective the case any more. With cloud development faster, cleverer, and more adaptable, various associations have moved their Data stockrooms in the cloud this year or have been hybridized, for instance using a cloud-based mix and neighborhood warehouses.

    Data and examination will end up being all the more:- Additional undertakings will be made to consolidate Data stages easily, giving broad show sheets to an association. Oneself help sensible gadgets market will similarly continue to make. We are really Data friendly in our age. As associations grant agents at different levels to inspect and separate the Data from their workstations and also handheld contraptions, the Data has become more impartial. Today, tries use self-organization business information (BI) models with advances in development and computing.

    More AI and ML, more NLP modernized:- The game plan of Data and exhibiting of Data will be more motorized. Consequently, this will incite much better and more exact disclosures. It helps associations with remaining before the resistance when they can take up the market floats early on.

    Customer Personalization Will Confirm Driver's Seat Consumers:- In Data science business components are at this point being changed. In the next year, we will see more associations focusing in on outfitting their customers with an outstandingly individualized inclusion with the suitable time during a customer's purchasing venture. With rising digitalization, clearly client personalization ought to be associated with a corporate technique. You need to meet where your clients are. To adequately adjust your picture, you need a "Tweaked Customer Experience Plan" considering Data. Taking everything into account, an "secured" client is a bright consumer

    Landscape Customer Data Platform will keep on creating:- Customer Data stages (CDP) have been significantly mentioned, given the rising digitalization that has been seen. A CDP is an awesome Data community point, where everything associated with Data meets from Data sources to information for customers. In dealing with a brand every client unavoidably pulls out behind the information. You may follow your impressions by riding the Internet or speaking with firms on various on the web and detached channels, similar to Websites, eCommerce stages, and in-store encounters.


    For the Data Scientist, the normal salary in India Rs. 752,656 per annum. Depending upon your talent and experience the salary package changes. The scope of the Data Scientist will increase immensely in the future and the demand for Data Scientist is going to be robust. So learn the Data Science Online Certification Course professionally and get the required hands-on skills to qualify yourself as a Data Scientist.

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Key Features

ACTE Ankara 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.


Syllabus of Data Science Certification Training in Ankara
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 Ankara 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.

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About Experienced Data Science Certification Trainer

  • Our Data Science Certification Training in Ankara. 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 Ankara from recognized IT organizations.

Data Science Certification Course Reviews

Our ACTE Ankara Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.



ACTE is the best training institute for Data science and Data Analytics in BTM Layout. The trainers are well experienced and the methodology of teaching is top notch. They provide practicals along with theoretical sessions for complete understanding of the concepts. They even provide placement assistance after course completion as well.


Software Engineer

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.


Best DATA SCIENCE training institute in Tambaram with Realtime client projects and dedicated support team. I have taken Data science training on this January and completely happy with their teachings, projects and job support after the course completion. It's a One stop destination for your data science And AI training in BTM Layout.



ACTE for your career switch to Data Science..They have well experienced Trainers in ACTE who can make you industry ready. Curriculum is quite unique and includes current industry needs. They give very good job assistance also.


Software Engineer

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

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Data Science Certification Course FAQs

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Call now: +91 93833 99991 and know the exciting offers available for you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    • Gives
    • For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Data Science 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's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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