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Data Science Certification Training in Poland

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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.
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  • 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 Poland?

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 Poland

Our Data Science Training in Poland has state-of-the-art labs and infrastructure to give you hands-on training. In addition, we provide certification training in Data Science. We have successfully taught and placed many of our students in big international organizations once they have completed the Data Science Training course. We give 100% placement help to our students. We provide Classroom Training, Weekend Training, and a Fast Song Route for fun Data Science Training in Poland. Students can select the most convenient journey times for them.

To outline data Data Science know-how and enhance data Data Science know-how undertaking management, begin with its life cycle. The first stage in the Data Science know-how pipeline workflow is the capture: gathering data, extracting it when necessary, and entering it into the system. Data warehousing, data cleansing, data processing, data staging, and data architecture are included in the maintenance degree.


Additional Info

Introduction of Data Science Online Certification :

Data processing follows and constitutes one of the data of Data Science know-how basics. It is in the course of data exploration and processing that data scientists stand other than data engineers. This degree includes data mining, data beauty and clustering, data modeling, and summarizing insights gleaned from the data—the strategies that create powerful data. Next comes data evaluation, and a similarly crucial degree. Here are data scientists' behavior exploratory and confirmatory Work, regression, predictive evaluation, qualitative evaluation, and textual content mining. This degree is why there may be no such component as cookie-cutter data Data Science know-how—even as it’s accomplished properly.

Roles of Data Science Online Training :

    “Data Science” refers to a huge series of established, semi-established, or unstructured heterogeneous data. Databases are generally not able to cope with such voluminous datasets. As said earlier, the vital element of Data Science is Data. “The bigger the data, the higher the insights,” as a rule of thumb goes. As a result, Data Science is an important component of the Data Science project.

    Data Science is characterized with the aid of using the beneficial useful resource of using its range and quantity, each of that is crucial for Data Science. Data Science captures the complicated styles from Data Science with the beneficial useful resource of using growing Machine Learning Models and Algorithms. Data Science is this kind of undertaking that may be achieved in nearly every corporation to treatment complicated problems. Every corporation applies Data Science to one-of-a-kind software with the view of fixing a one-of-a-kind problem. Some agencies rely upon Data Science and Machine Learning strategies to treatment a great set of problems, which, otherwise, couldn't be solved. Some of such packages of Data Science and the agencies withinside the back of them are indexed below.

  • Internet Search Results (Google):
  • When a person searches for something on Google, complicated Machine Learning algorithms decide which may be the maximum applicable consequences for the quest duration (s). These algorithms assist to rank pages such that the maximum applicable data are supplied to the person at the pressing of a button.

  • Recommendation Engine (Spotify):
  • Spotify is a track streaming issuer this is pretty famous for its cappotential to propose tracks consistent with the flavor of the person. This is a wonderful instance of Data Science at play. Spotify’s algorithms use the data generated with the beneficial useful resource of using all and sundry through the years to take a look at the person’s flavor in track and propose him/her with comparable track withinside the destiny. This we could the corporation draw greater customers because it is greater to be had for the person to apply Spotify because it does not call for a whole lot of attention.

  • Intelligent Digital Assistants (Google Assistant):
  • Google Assistant, similar to unique voice or textual content-primarily based virtual assistants (furthermore called chatbots) is one instance of superior Machine Learning algorithms placed to apply. These algorithms can convert the speech of a person (regardless of one-of-a-kind accents and languages) to textual content, understand the context of the textual content/command, and offer applicable data or carry out a favored task, all honestly with the beneficial useful resource of using talking to the device.

  • Spam Filter (Gmail):
  • Another key software of Data Science which we use in our ordinary life is the junk mail filters in our emails. These filters routinely separate the junk mail emails from the rest, successfully giving the person a miles cleaner email revel in. Just similar to the unique packages, Data Science is the vital element constructing block here.

  • Abusive Content and Hate Speech Filter (Facebook):
  • Similar to the unsolicited mail filter, Facebook and distinctive social media structures use Data Science and Machine Learning algorithms to clean out abusive and age-restricted content material fabric from the unintended audience.

  • Automatic Piracy Detection (YouTube):
  • Most movies that might be probably uploaded to YouTube are actual content material fabric material created with the beneficial useful resource of using content material fabric material creators. However, pretty often, pirated and copied movies also are uploaded to YouTube, this is their policy. Due to the sheer quantity of ordinary uploads, it isn't feasible to manually encounter and takedown such pirated movies. This is wherein Data Science is used to routinely encounter pirated movies and eliminate them from the platform.


What is Data Science?

Data Science is a multidisciplinary undertaking that makes use of scientific inference and mathematical algorithms to extract massive statistics and insights from a huge quantity of established and unstructured data. These algorithms are carried out via laptop packages which may be generally run on effective hardware because it calls for a huge quantity of processing. Data Science is an aggregate of statistical mathematics, device gaining knowledge of, data evaluation and visualization, area statistics, and laptop Data Science know-how.

As it is obvious from the name, the maximum crucial element of Data Science is “Data” itself. No quantity of algorithmic computation can draw massive insights from incorrect data. Data Data Science know-how includes severa styles of data, for instance, photo data, textual content data, video data, time-based data, etc. Our Data Science Training in Poland is well-geared up with labs and wonderful infrastructure to provide you hands-on training. In addition, we provide Data Science certification training.

Trends Of Data Data Science:

    The undertaking of Data Science has been developing ever because of its onset withinside the period. With time, the growing modern generation is being included in the undertaking. Some of such greater ultra-contemporary-day additions are indexed below:

  • Artificial Intelligence:
  • Machine Learning has been one of the vast factors of Data Science. However, with the extended parallel compute capabilities, Deep Learning has been the contemporary day and one of the maximum huge additions to the Data Science undertaking.

  • Edge Computing:
  • Edge computing is these days an advanced idea and is associated with IoT (Internet of Things). Edge computing places the Data Science pipeline of data series, shipping, and processing withinside the route of the shipping of data. This is feasible via IoT and has these days been added to be part of Data Science.

  • Security:
  • Security has been a primary assignment withinside the virtual space. Malware injection and the idea of hacking are pretty now not unusualplace and all virtual structures are prone to it. Fortunately, there were few ultra-contemporary-day Data Science enhancements that workout Data Science strategies to save you the exploitation of virtual structures. For instance, Machine Learning strategies have established the greater functionality of detecting laptop viruses or malware even as in assessment to standard algorithms.


Skills required to grow to be a Data Scientist:

    As said withinside the preceding section, Data Science is a complicated undertaking. Hence, it calls for the mastery of more than one sub-fields, which collectively upload as a bargain due to the fact the complete statistics are required to be a Data Scientist.

    1. Mathematics:

    The first and the maximum crucial undertaking of observation to emerge as a Data Scientist is mathematics; greater especially, Probability and Statistics, Linear Algebra, and a few primary Calculus.

    2. Machine Learning Frameworks:

    Machine Learning is a crucial part of Data Science and its implementation includes great libraries and frameworks, the statistics of which may be crucial for any Data Scientist. Here, a number of the maximum normally used Machine Learning frameworks are indexed.

  • Numpy:
  • This is a library that permits the easy implementation of linear algebra and data manipulation.

  • Pandas:
  • This library is used to load, regulate and keep data. This is likewise implemented in data wrangling.

  • Matplotlib:
  • This is one of the maximum normally used libraries for data visualization.

  • Seaborn:
  • This is a wrapper over Matplotlib, this is used to visualize greater complicated data.

  • Sklearn:
  • TThis is used to use and placed into effect maximum of the device gaining knowledge of algorithms and data preprocessing strategies.

  • Tensorflow:
  • This is a deep getting-to-apprehend framework sponsored with the beneficial useful resource of using Google and permits easy implementation of severa styles of neural networks.

  • PyTorch:
  • Similar to TensorFlow, this is furthermore a deep gaining knowledge of framework this is often used.

  • Keras:
  • This is a wrapper that works collectively with TensorFlow and permits especially easy implementation of Deep Learning strategies.

  • OpenCV:
  • This is a laptop imaginative and prescient framework and is generally used for Image Processing and image manipulation.

  • Statistics:
  • It is crucial in EDA and growing algorithms to behavior statistical inference at the data. Additionally, maximum Machine Learning Algorithms use data as their essential constructing blocks.

  • Linear Algebra:
  • Working with a large kind of data technique running with high-dimensional matrices and matrix operations. The data that the version takes in and the simplest that it offers as output are withinside the shape of matrices and consequently any operation this is accomplished on them makes use of the basics of Linear Algebra.

  • Calculus:
  • Since Data Science does consist of Deep Learning, calculus is of huge significance. In Deep Learning, calculation of Gradient may be very crucial and is accomplished at each step of computation in Neural Networks. This calls for valid statistics on differential and essential calculus.

3. Programming Languages (R and Python):

Even even though any programming language may be used for any shape of logical use case, which of the route, consists of Data Science; but, the maximum normally used languages are R and Python. Both of those languages are open supply and consequently have large network support, have more than one library advanced maintaining Data Science in mind, and are especially easy to take a look at and use. Without the statistics of programming languages, a Data Scientist can't work out any shape of algorithmic or mathematical statistics of the data.

4. Proper Programming Environment:

Since sound programming statistics is one of the key necessities for Data Science, there wants to be an to be had a platform to put in writing and execute the code. This platform is called the IDE or Integrated Development Environment. There are numerous IDEs to pick out from, and a number of them were especially advanced for Data Science. This article talks approximately the Top 10 Python IDEs.

5. SQL:

Databases are of huge significance withinside the undertaking of Data Science because they will be the maximum appropriate technique for storing data. Thorough statistics of 1 or greater database generation like MySQL, MariaDB, PostgreSQL, MS SQL Server, MongoDB, Oracle NoSQL, etc.

6. Algorithmic Knowledge:

Even even though Data Science generally does not include the improvement and layout of Algorithms like some distinctive packages of Computer Science does, it is even though crucial for a Data Scientist to have legitimate statistics of Algorithms. This is due to the fact, at the prevent of the day, Data Scientists are programmers who're predicted to increase packages that might derive massive insights from data. Having algorithmic statistics we could the Data Scientist write down massive green code, which saves every time and deliver and consequently is as an alternative value.


Future of Data Science Certification Training :

Data Science is an ever-developing undertaking and is predicted to grow in a call for withinside the foreseeable destiny. Some of the vital element adjustments are indexed below.

Data: With the novel growth of the era of data, the overall normal overall performance of the predictive algorithms goes to enhance through the years as greater data are to be had to attract inference upon. This phenomenon is fueled with the beneficial useful resource of using the boom of Social Media and IoT-primarily based devices, which generate loads greater data.

Algorithms:Machine Learning algorithms like Genetic Algorithms and Reinforcement Learning algorithms are predicted to enhance through the years inflicting greater smart structures.

Distributed Computing: With the enhancements of the blockchain generation, TPU (Tensor Processing Unit) improvement, and quicker GPU (Graphics Processing Unit) to be had withinside the cloud, Data Science sees a destiny wherein greater effective computational hardware aids the algorithms of growing complexity.

Career Growth of Data Science Certification Training in Poland :

The 21 century might be dominated by the beneficial useful resource of using data. Data Science has grown to be a crucial part of many agencies and industries. It presents valuable insights into purchaser conduct which could result in extended conversions, greater real marketplace evaluation for aggressive benefit in pricing techniques or product improvement, improved operational efficiency, and minimized hazard publicity via correct forecasting models.

Advantages Of Data Science Certification Training :

1. Increases commercial enterprise predictability

1. Increases industrial organization predictability increases enterprise corporation predictability is a corporation invests in structuring its data, it could paintings with what we name predictive evaluation. With the assist of the data scientists, it is feasible to apply generation together with Machine Learning and Artificial Intelligence to Work with the data that the corporation has and, in this way, perform greater specific analyses of what's to come. Thus, you grow the predictability of the commercial corporation and may make selections these days in a way to affect the destiny of your enterprise corporation.

2. Ensures real-time intelligence

Ensures actual-time intelligence ensures actual-time intelligence data of scientists can Work with RPA experts to pick out out the assets of the one-of-a-kind data in their enterprise corporation and create automatic dashboards, which might be searching for the maximum of those data in actual-time in a covered way. This intelligence is crucial for the managers of your corporation to make greater correct and quicker selections.

3. Favors the advertising and income place

Favors the marketing and marketing and earnings place favors the advertising and marketing and advertising and marketing and earnings area statistics-pushed Marketing is a well-known duration these days. The motive is simple: only with data, we can provide solutions, communications, and merchandise that might be probable steady with purchaser expectations. As we've were given seen, data scientists can combine data from simply taken into consideration certainly one of the type assets, bringing even greater correct insights to their team. This is feasible with Data Science.

4. Improves facts security

Improves records security improves data security of the advantages of Data Science are the Work is accomplished withinside the area of ​​data security. In that sense, there may be a worldwide of possibilities. The data scientists Work on fraud prevention structures, for instance, to maintain your corporation’s clients safer. On the possibility hand, he also can take a look at ordinary styles of conduct in a corporation’s structures to pick out out out feasible architectural flaws.

5. Helps interpret complicated facts

Helps interpret complex records helps interpret complicated data statistics Science is an exceptional answer even as we need to move one-of-a-kind data to understand the commercial corporation and the marketplace higher. Depending on the gadget we use to accumulate data, we can combine data from “physical” and digital assets for higher visualization.

6. Facilitates the decision-making process

Facilitates the decision-making system facilitates the selection-making system of the route, from what we've were given uncovered so far, you want to already believe that one of the advantages of Data Science is enhancing the selection-making system. This is due to the fact we can create a gadget to view data in actual time, permitting greater agility for enterprise corporation managers. This is accomplished each with the beneficial useful resource of using dashboards and with the beneficial useful resource of using the projections which might be feasible with the data scientist’s remedy of data.

Need of SQL in Data Science Certification :

  • SQL (Structured Query Language) is used for appearing diverse operations at the statistics saved withinside the databases like updating records, deleting records, developing and enhancing tables, views, etc. SQL is likewise the usual for the modern huge statistics structures that use SQL as their key API for his or her relational databases.
  • Data Science is the all-around look at statistics. To paintings with statistics, we want to extract it from the database. This is wherein SQL comes into the picture. Relational Database Management is a vital part of Data Science. A Data Scientist can control, define, manipulate, create, and question the database through the use of SQL commands.
  • Many cutting-edge industries have ready their merchandise statistics control with NoSQL generation but, SQL stays the proper preference for plenty of commercial enterprise intelligence gear and in-workplace operations.
  • Many of the Database structures are modeled after SQL. This is why it has come to be popular for plenty of database structures. Modern huge statistics structures like Hadoop, Spark additionally employ SQL best for keeping the relational database structures and processing dependent statistics.

Tools Of Data Science online Training :

    A Data Scientist is in charge of obtaining, manipulating, pre-processing, and predicting information from data. He'll need a variety of statistical tools and computer languages to accomplish so. We'll go through some of the Data Science Tools that Data Scientists utilize to carry out their data operations in this post. We'll learn about the tools' major features, advantages, and a comparison of different data science tools.

  • SAS
  • Apache Spark
  • BigML
  • D3.js
  • MATLAB
  • Excel
  • ggplot2
  • Tableau
  • Jupyter
  • Matplotlib
  • NLTK
  • Scikit-learn
  • TensorFlow
  • Weka

Salaries of a Data Scientist In Poland:

The Data Science undertaking is one of the maximum paying jobs withinside the software program software area. It is likewise the nice paying with the bottom quantity of applicable Work revel in even as in assessment to 3 distinctive demanding situations withinside the software program software area, as established withinside the parent.

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Key Features

ACTE Poland 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 Course in Poland
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 Poland 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 Poland. 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 Poland from recognized IT organizations.

Data Science Certification Course Reviews

Our ACTE Poland 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.

Suresh

Software Engineer

Amazing experience. I was taught by Hari sir. He holds in depth knowledge of the subject matter and covered all the important topics that are required to be a Data Scientist in just a span of 3 months. His notes are notes quite good and helpful for interviews.I am glad I took it as it gives a quick start to your career in Data Science. Thanks ACTE at Velachery

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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