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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 and Advance tools, but also gain exposure to Industry best practices, Aptitude & SoftSkills.
- Experienced Trainers and Lab Facility.
- IBM Data Science 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, significance of Data Science in today’s digitally-driven world, components of the Data Science 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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This is How ACTE Students Prepare for Better Jobs
About Data Science Training Course in OMR
Data Science course in ACTE helps you master Data Analytics, Business Analytics, Data Modelling, Machine Learning algorithms, K-Means Clustering, Naïve Bayes, etc. This Data Science training in ACTE will help you learn R statistical computing, building recommendation engine for e-commerce, recommending movies and deploy market basket analysis in the retail sector. Get the best online data science certification in ACTE from top data scientists.
Most Job Oriented DataScience Modules Covered
Statistics, Naive Bayes
Linear Algebra, CART
Programming, Neural Networks
Data Mining, Visualization
Is Data science be an good career option?
Most of the peoples need good job and good salary while, Learning data science will raise your probabilities of acquiring a good job and the well maintained career option.... The demand for a data scientist is growing day by day since there are not many experts in this field. Learning data science will provide you the chance of finding a well decent job in this market where they are particularly required right now. Data Science a highly lucrative career option.
Is it worth being a data scientist?
Meanwhile, For several years data scientist has been ranked as one of the top jobs in india and around the world, in terms of pay, job demand, and satisfaction. Companies are increasingly using the data scientist title for other similar roles such as data analyst. "I think that what we're seeing is a little bit of the standardization and the professionalization of data science," "The past ten years have been a bit of the Wild West when it comes to data science.
Is Data Science in demand?
While, demand for data science skills is growing exponentially, according to job sites. The supply of skilled applicants, however, is growing at a higher pace. It's a great time to be a data scientist entering the job market. ... "More employers than ever are looking to hire data scientists." it's a great time to be a data scientist entering the job market. That's according to recent data from job sites Indeed and Dice.
Will ACTE Help Me With Placements After My Data science Course Completion?
We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings in data science. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.
Is Data Science a good field?
Data science is a good field, skilled data science are some of the most sought-after professionals in the world. Because the demand is so high and strong, and the supply of people who can truly do this job well is so limited, data science is a command huge salary and excellent perks, some peoples can able even at the entry level. Many companies also label data analysts as information scientists. This classification typically involves working with a company’s proprietary database.
What is the difference between data science and big data?
So coming to this there are not a great different. Data Science is the field that comprises of everything that related to data cleansing, data mining, data preparation, and data analysis. Big Data refers to the vast volume of data that is difficult to store and process in real-time. This data can used to analyse insights that can lead to better decision making. Data Science algorithms are used in industries such as internet searches, search recommendations, advertisements.
Does Data Science require coding?
Analysts and researchers have been around long before big data, which is why data analyst roles are well defined. Data analysts do not need to have advanced coding skills, but have experience with analytics software, data visualization software, and data management programs.
Will I Be Given Sufficient Practical Training In Data science?
Our courseware is designed to give a hands-on approach to the students in Data science. 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.
Is it worth learning data science in 2020?
Data science Is giving world wide job opporutunites
Data science remains to be one of the best jobs in 2020. According to McKinsey, the US will be facing a shortfall of 250,000 data scientists by 2024. Though the jobs market is in constant change, a data scientist job still hits the top list. If you are interested in learning data science, that's awesome. With more and more things being driven by data we need more people to understand what's needed to produce successful and safe data science machine learning projects. ... Data science is totally worth doing.
Does data science have a future?
Data Scientists Have a great future. Research shows 94 percent of data science graduates have gotten jobs in the field since 2011. One of the indicators that data science careers are well suited for the future is the dramatic increase in data science job. The demand for a data science is growing day by day since there are not many experts in this field. Learning data science will provide you the chance of finding a decent job and the bright future in this market where they are particularly required right now.
Top reasons to consider a career in Data science?
The potential for quantum computing and data science is huge in the future. Machine Learning can also process the information much faster with its accelerated learning and advanced capabilities. Based on this, the time required for solving complex problems significantly reduced. Companies require skilled Data Scientists to process and analyses their data. They not only analyse the data but also improve its quality. Therefore, Data Science deals with enriching data and making it better for their company
Purpose of Data Science
we will go through the role that a Data Scientist plays. There is a veil of mystery surrounding Data Science.
- While the buzzword of Data Science has been circulating for a while, very few people know about the real purpose of being a Data Scientist.
- We will go through the various responsibilities that a Data Scientist must fulfil and understand as to what industries seek from employing Data Scientists.
we will look at various types of industries which employ Data Scientists to make better decisions. So, let’s explore the purpose of Data Science.
- The principal purpose of Data Science is to find patterns within data. It uses various statistical techniquesto analyze and draw insights from the data.
- From data extraction, wrangling and pre-processing, a Data Scientist must scrutinize the data thoroughly. Then, he has the responsibility of making predictions from the data.
- The goal of a Data Scientist is to derive conclusions from the data. Through these conclusions, he is able to assist companies in making smarter business decisions. We will divide this blog in various sections to understand the role of a Data Scientist in more detail.
Why Data Matters
Data is the new electricity. We are living in the age of the fourth industrial revolution.This is the era of Artificial Intelligence and Big Data. There is a massive data explosion that has resulted in the culmination of new technologies and smarter products.
Around 2.5 exabytes of Data is created each day. The need for data has risen tremendously in the last decade. Many companies have centred their business on data. Data has created new sectors in the IT industry. However,
- Why do we need Data?
- Why do industries need Data?
- What makes data a precious commodity?
The answer to these questions lies in the way companies have sought to transform their products.
- Data Science is a very recent terminology. Before Data Science, we had statisticians. These statisticians experienced in qualitative analysis of data and companies employed them to analyze their overall performance and sales.
- With the advent of a computing process, cloud storage, and analytical tools, the field of computer science merged with statistics. This gave birth to Data Science.
- Earlydata analytics based on surveying and finding solutions to public problems. For example, a survey regarding a number of children in a district would lead to a decision of development of the school in that area. With the help of computers, the decision-making process has been simplified.
- As a result, computers could solve more complex statistical problems. As Data started to proliferate, companies started to realize its value. Its importance reflected in the many products designed to boost customer experiences. Industries sought experts who could tap the potential that data holstered.
- Data could help them make the right business decisions and maximize their profits. Moreover, it gave the company an opportunity to examine and act according to customer behaviour based on their purchasing patterns. Data helped companies boost their revenue model and helped them craft a better-quality product for clients.
- Data is to products what electricity is to household gadgets. We need data to engineer the products that cater to the users. It is what drives the product and makes it usable.
- A Data Scientist is like a sculptor. He chisels the data to create something meaningful out of it. While it can be a tedious task, a Data Scientist needs to have the right expertise to deliver the results.
ACTE OMR offers Data Science 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
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 Course in OMRModule 1: Introduction to Data Science with R
- What is Data Science, significance of Data Science in today’s digitally-driven world, applications of Data Science, lifecycle of Data Science, components of the Data Science 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- Introduction to Support Vector Machine (SVM), Data classification using SVM, SVM Algorithms using Separable and Inseparable cases, Linear SVM for identifying margin hyperplane.
- 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.
- 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.
- 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.
Hands-on Real Time Data Science Projects
Wallmart Sales Data Set
Retail is another industry that extensively uses analytics to optimize business processes.
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 OMR 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 training course content, we will arrange the interview calls to students & prepare them to F2F interaction
- Data Science 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
a physical version of your officially branded and security-marked Certificate.
About Experienced Data Science Trainer
- Our Data Science Training in OMR. 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 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 training to the students.
- We have received various prestigious awards for Data Science Training in OMR from recognized IT organizations.
Data Science Course Reviews
ACTE is the best training institute for Data science and Data Analytics in OMR. 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.
It's to good institute and its more helpful for people who are suffering from jobs. They will help u a lots by teaching Data Science and make to learn us more things from ACTE institute in OMR and also they will give u a good placements also.
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 OMR.
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.
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.
Data Science Course FAQs
Looking for better Discount Price?
Does ACTE provide placement?
- 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
Is ACTE certification good?
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
Work On Live Projects?
- The entire Data Science 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
Who are the Trainers?
What if I miss one (or) more class?
What are the modes of training offered for this Data Science Course?
Why Should I Learn Data Science Course At ACTE?
- Data Science Course in ACTE is designed & conducted by Data Science experts with 10+ years of experience in the Data Science 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