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Data Science Certification Training in Doha

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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.
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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 Doha?

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 Doha

Data science in Doha can also be defined as a field concerned with the processes and systems used to extract data in various forms and from various resources, whether the data is unstructured or structured.It is the ability to reveal insights and trends hidden (or abstracted) behind data. With these insights, you can make strategic decisions for a business or institution.The definition and name were coined in the 1980s and 1990s when some professors, IT professionals, and Sceience were reviewing the statistics curriculum and decided it would be better to call it data science and then data analytic.

The study of data is known as data science. Physical sciences, like biological sciences, are concerned with the study of physical reactions. Data is real, and it has real properties that we must study if we are to work with it. Data Science entails the use of data as well as some indicators.It is a procedure, not a single event. It is the process of using data to comprehend a wide range of topics in order to comprehend the world. Assume you have a model or proposed explanation for a problem and you are attempting to validate that proposed explanation or model using your data. It is the process of converting data into a storey. As a result, use storytelling to generate insight.

Additional Info


This introductory course provides a high-level overview of key Data Science topics. A fundamental understanding of Data Science from both a business and technological standpoint is provided, as well as an overview of common benefits, challenges, and adoption issues. This course will teach you the fundamentals of data science as well as how to use Python, a powerful open source tool. You will learn about exploratory data analysis, statistics fundamentals, hypothesis testing, regression and classification modelling techniques, and machine learning. The course's final project and interview preparation will prepare you for the workforce.

Data Science in Doha are in high demand, having been named the sexiest career of the twenty-first century by none other than the Harvard Business Review. Data Sceience have been shown to earn up to 36% more in base pay than other predictive analytics professionals. According to Glassdoor, the national average salary for a Data Sceiencein the United States is $1,39,840.KnowledgeHut's Data Science Foundation course will help both new and experienced professionals gain a thorough understanding of the subject and advance their careers.

Career Path of Data Science:

    Sceiencein Machine Learning:

  • Typical Job Requirements: Investigate novel data approaches and algorithms for use in adaptive systems, such as supervised, unsupervised, and deep learning techniques.
  • Machine learning Sceience are frequently referred to as Research Sceience or Research Engineers.
  • Architect of Applications:

  • Typical Job Requirements: Monitor the behaviour of business applications and how they interact with one another and with users.
  • Applications architects are also responsible for designing application architecture, which includes building components such as user interface and infrastructure.
  • Architect, Enterprise:

  • Typical Job Requirements: An enterprise architect is in charge of aligning an organization's strategy with the technology required to achieve its goals.
  • In order to do so, they must have a thorough understanding of the business and its technological requirements in order to design the systems architecture required to meet those requirements.
  • Data Engineer:

  • Typical Job Requirements: Ensure that data solutions are designed for performance and that analytics applications are designed for multiple platforms.
  • In addition to developing new database systems, data architects frequently seek ways to improve the performance and functionality of existing systems, as well as work to provide database administrators with access.
  • Infrastructure Designer:

  • Typical Job Requirements: Ensure that all business systems are operating at peak efficiency and that you can support the development of new technologies and system requirements.
  • Cloud Infrastructure Architect is a similar job title that oversees a company's cloud computing strategy.
  • Engineer, Data:

  • Typical Job Requirements: Perform batch or real-time processing on collected and stored data.
  • Data engineers are also in charge of creating and maintaining data pipelines within an organisation, which creates a robust and interconnected data ecosystem and makes information available to data Sceience.
  • Developer of Business Intelligence (BI):

  • Business intelligence developers design and develop strategies to help business users quickly find the information they need to make better business decisions.
  • They are extremely data-savvy and use BI tools or develop custom BI analytic applications to help end-users understand their systems.

The following are the roles and responsibilities of a data science:

  • Data mining is the process of extracting useful data from valuable data sources.
  • Selecting features, creating and optimising classifiers with machine learning tools.
  • Preprocessing both structured and unstructured data.
  • Improving data collection procedures to include all pertinent information for the development of analytic systems.
  • Data processing, cleansing, and validation to ensure the integrity of data for analysis.
  • Analyzing large amounts of data to discover patterns and solutions.
  • Prediction systems and machine learning algorithms are being developed.
  • Results must be presented in a clear and concise manner.
  • Provide solutions and strategies for dealing with business challenges.
  • Work with the business and IT teams to achieve your goals.

To become a data Sceience you must have the following skills:

  • Programming abilities – knowledge of statistical programming languages such as R and Python, as well as database query languages such as SQL, Hive, and Pig, is preferred.
  • Knowledge of Scala, Java, or C++ is advantageous.
  • Statistics – Excellent applied statistical skills, such as knowledge of statistical tests, distributions, regression, maximum likelihood estimators, and so on.
  • Statistics knowledge is essential for data-driven businesses.
  • Machine Learning – thorough understanding of machine learning methods such as k-Nearest Neighbors, Naive Bayes, SVM, and Decision Forests.
  • Strong Math Skills (Multivariable Calculus and Linear Algebra) - Understanding the fundamentals of Multivariable Calculus and Linear Algebra is critical because they serve as the foundation for many predictive performance or algorithm optimization techniques.
  • Data Wrangling – The ability to deal with flaws in data is an important aspect of a data Sceiences job description.
  • Experience with data visualisation tools such as matplotlib, ggplot, d3.js, and Tableau, which aid in visually encoding data.
  • Excellent Communication Skills – It is critical to be able to explain findings to both technical and non-technical audiences.
  • Strong background in software engineering.
  • Hands-on experience with data science tools is required.
  • Ability to solve problems.
  • Analytical mind with excellent business acumen.
  • A bachelor's degree in computer science, engineering, or a related field is preferred.
  • Experience as a Data Analyst or Data Sceienceis required.

Advantages of Data Science Training:

    1.Improves commercial predictability:

  • When a company invests in data structuring, it can use what is known as predictive analysis.
  • With the assistance of a data Sceience it is possible to use technologies such as Machine Learning and Artificial Intelligence to work with the company's data and, as a result, perform more precise analyses of what is to come.
  • As a result, you increase business predictability and can make decisions today that will positively impact your company's future.
  • 2.Provides near-real-time intelligence:

  • The data Sceiencecan collaborate with RPA professionals to identify their company's various data sources and create automated dashboards that search all of this data in real-time and in an integrated manner.
  • This intelligence is critical for your company's managers to make more accurate and timely decisions.
  • 3.Preferential treatment for marketing and sales:

  • Data-driven Nowadays, marketing is a generic term. The reason is simple: we can only offer solutions, communications, and products that are truly in line with customer expectations if we have data.
  • As we've seen, data Sceience can combine data from various sources to provide their teams with even more accurate insights.
  • Can you imagine having access to the entire customer journey map, taking into account all of the interactions your customers had with your brand? Data Science makes this possible.
  • 4. Enhances data security:

  • The work done in the area of data security is one of the advantages of Data Science.
  • In that sense, there is an infinite number of possibilities.
  • Data Sceience, for example, work on fraud prevention systems to keep your company's customers safe.
  • He can, on the other hand, study recurring patterns of behaviour in a company's systems to identify potential architectural flaws.
  • 5. Aids in the interpretation of complex data:

  • When we want to cross different data sets to better understand the business and the market, Data Science is a great solution.
  • We can mix data from "physical" and "virtual" sources for better visualisation depending on the tools we use to collect data.
  • 6. Makes the decision-making process easier:

  • Of course, based on what we've shown so far, you can already imagine that one of the benefits of Data Science is improved decision-making.
  • This is because we can create tools to view data in real-time, allowing business managers to be more agile.
  • This is accomplished through the use of dashboards as well as projections made possible by the data Sceiences treatment of data.

The following are the top 15 data science certifications:

  • Analytics Professional Certification (CAP).
  • Data Analyst Cloudera Certified Associate (CCA).
  • Data Engineer, Cloudera Certified Professional (CCP).
  • Senior Data Sceienceat the Data Science Council of America (DASCA) (SDS).
  • Principle Data Sceienceat the Data Science Council of America (DASCA) (PDS).
  • Data Science Track at Dell EMC (EMCDS).
  • Certification as a Google Professional Data Engineer.
  • Professional Certificate in Data Science from IBM.
  • Azure AI Fundamentals is a Microsoft Certified Professional programme.
  • Azure Data SceienceAssociate is a Microsoft Certified Professional.
  • Certified Data SceiencePositions Available (Open CDS).
  • SAS AI & Machine Learning Professional certification.
  • SAS Big Data Professional certification.
  • SAS Data SceienceCertification.
  • Tensorflow Developer Certification.

Industry Trends:

    1. Deepfake Explosion:

  • Deepfakes employ artificial intelligence to manipulate or create content in order to impersonate another person.
  • Often, this is an image or video of one person that has been altered to look like someone else.
  • 2. Additional Python Applications:

  • Python has a plethora of free data science libraries, such as Pandas, and machine learning libraries, such as Scikit-learn.
  • It is even capable of being used to create blockchain applications.
  • When you combine this with a user-friendly learning curve for beginners, you have a recipe for success.
  • According to the analyst firm RedMonk, Python is now the third most popular language in general.
  • And the popularity growth trend indicates that it is on track to become the number one neologism in the world.
  • 3. Increased Demand for Full-Stack AI Solutions:

  • Dataiku, an enterprise AI company, is now valued at $1.4 billion (according to TechCrunch), following Google's purchase of a stake in the company in December 2019.
  • The AI startup assists enterprise customers in cleaning large data sets and developing machine learning models.
  • Companies such as General Electric and Unilever can gain valuable, deep learning insights from their massive amounts of data in this manner.
  • Additionally, important data management tasks should be automated.
  • Previously, businesses had to seek expertise in all aspects of the process and piece it together on their own.
  • 4. Businesses Hire More Data Analysts:

  • It is also becoming more common for data professionals to be involved in the output process.
  • Because AI-generated results are not always reliable or accurate, machine learning companies frequently employ humans to clean up the final data.
  • And write up their findings in a way that non-tech stakeholders can understand.
  • Data science and machine learning methods in the 2020s will be less artificial and automated than previously anticipated.
  • Artificial intelligence with human-in-the-loop and augmented intelligence will most likely become a big trend in data science.
  • 5. Kaggle Adds Data Sceience:

  • Many aspiring data Sceience now begin their machine learning journey with Kaggle.
  • And live-stream the progress of their machine learning projects.
  • Users can even share data sets and compete in data science competitions using neural networks.
  • Alternatively, collaborate with other data Sceience to create models in Kaggle's web-based data science workbench.

Payscale of Data Science in Doha:

1. The average salary for a data science in Doha is $698,412.

2. With less than a year of experience, an entry-level data Science can earn around $500,000 per year.

3. Early-career data Sceience with 1 to 4 years of experience earn around 610,811 per year.

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Key Features

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

Data Science Certification Course Reviews

Our ACTE Doha 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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