- Beginner & Advanced level Classes.
- Hands-On Learning in Data Science.
- Best Practice for interview Preparation Techniques in Data Science.
- Lifetime Access for Student’s Portal, Study Materials, Videos & Top MNC Interview Question.
- Affordable Fees with Best curriculum Designed by Industrial Data Science Expert.
- Delivered by 9+ years of Data Science Certified Expert | 12402+ Students Trained & 350+ Recruiting Clients.
- Next Data Science Batch to Begin this week – Enroll Your Name Now!
(Class 1Hr - 1:30Hrs) / Per Session
(Class 1Hr - 1:30Hrs) / Per Session
(Class 3hr - 3:30Hrs) / Per Session
(Class 4:30Hr - 5:00Hrs) / Per Session
Can't find a batch? Pick your own schedule
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 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.
- START YOUR CAREER WITH DATA SCIENCE COURSE THAT GETS YOU A JOB OF UPTO 5 LACS IN JUST 60 DAYS!
- Classroom Batch Training
- One To One Training
- Online Training
- Customized Training
- Enroll Now
This is How ACTE Students Prepare for Better Jobs
About Data Science Training Course in Anna Nagar
Most Job Oriented DataScience Modules Covered
- R ProgrammmingPython, SAS Artifical Intelligence
- Deep LearningMachine Learning Statistics, Naive Bayes
- Linear Algebra, CARTProgramming, Neural Networks Data Mining, Visualization
Is Data science be an good career option?
Is it worth being a data scientist?
Is Data Science in demand?
Will ACTE Help Me With Placements After My Data science Course Completion?
Is Data Science a good field?
What is the difference between data science and big data?
Does Data Science require coding?
Will I Be Given Sufficient Practical Training In Data science?
Is it worth learning data science in 2020?
Does data science have a future?
Top reasons to consider a career in Data science?
Importance of Data Science
- Data is one of the important features of every organization because it helps business leaders to make decisions based on facts, statistical numbers and trends. Due to this growing scope of data, data science came into picture which is a multidisciplinary field. It uses scientific approaches, procedure, algorithms, and framework to extract the knowledge and insight from a huge amount of data. The extracted data can be either structured or unstructured.
- Data science is a concept to bring together ideas, data examination, Machine Learning, and their related strategies to comprehend and dissect genuine phenomena with data. Data science is an extension of various data analysis fields such as data mining, statistics, predictive analysis and many more. Data Science is a huge field that uses a lot of methods and concepts which belongs to other fields like information science, statistics, mathematics, and computer science. Some of the techniques utilized in Data Science encompasses machine learning, visualization, pattern recognition, probability model, data engineering, signal processing, etc.
- The developments of plenty of data have given enormous importance to many features of Data science particularly big data. But data science is not limited to big data alone as big data solutions concentrated more on organizing and pre-processing the data instead of analysing them. Also, due to Machine Learning, the importance and growth of data science has been improved.
- Let’ first know about from where the Data Science is originated. From the past few years, Data Science is utilized in many industries such as farming, risk management, fraud recognition, marketing optimization, and public policy, etc. With the help of machine learning, statistics, data preparation and predictive analysis, data science attempts to resolve many problems within individual sectors and the budget. Data science focuses on the utilization of general strategies while not ever changing it application, regardless of the domain.
- This method is entirely different from traditional statistics which incline to concentrate on giving solutions that are specific to explicit sectors or domains. The conventional approaches rely on giving solutions which are tailored to each problem instead of applying the quality solution. Today, Data science has extensive ramifications in numerous fields, i.e., in theoretical and applied research areas such as machine interpretation, speech recognition, advanced economy and also in the fields like healthcare, social science, medical informatics. Data Science influences the growth and improvements of the product by providing a lot of intelligence about customers and operations, by using methods such as data mining and data analysis.
- With the help of Data Science, the companies will be able to recognize their client in a more improved and enhanced way. Clients are the foundation of any product and play an essential role in their success and failure. Data Science enables companies to connect with their customers in a modified manner and thus confirms the better quality and power of the product.
- Data Science allows products to tell their story powerfully and engagingly. This is one of the reasons which makes it popular. When product and companies use this data inclusively, they can share their story with their viewers and thus creating better product connections.
- One of the important features of Data Science is that its results can be applied to almost all types of industries such as travel, healthcare and education. With the help of Data Science, the industries can analyse their challenges easily and can also address them effectively.
- Presently, data science is available in almost all the fields and there is a vast amount of data present in the world today and if it is used properly it can lead the product to the success or failure. If data is used correctly it will hold the importance for achieving goals for the product in the future.
- Big data is continuously emerging and growing. Using various tools which are developed regularly, big data helps the organization to resolve complex issues related to IT, human resource and resource management efficiently and successfully.
- Data science is gaining popularity in every industry and thus playing a significant role in functioning and growth of any product. Therefore, the requirement of data scientist is also increased as they have to perform an important task of handling data and delivering solutions for the specific problems.
- Data science also influenced the retail industries. Let’s take an example to understand this, the older people were having a fantastic interaction with the local seller. The seller was also capable of fulfilling the requirements of the clients in a personalized way. But now due to the emergence and increase of supermarkets, this attention got lost. But with the help of data analytics, it is possible for the sellers to connect with their clients.
- Data Science helps organizations to build this connection with the clients. With the help of data science, organizations and their products will be able to create a better and deep understanding of how customers can utilize their products.
- 40 Hours Course Duration
- 100% Job Oriented Training
- Industry Expert Faculties
- Free Demo Class Available
- Completed 500+ Batches
- Certification Guidance
Syllabus of Data Science Course in Anna NagarModule 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
- 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
Complete Your Coursea downloadable Certificate in PDF format, immediately available to you when you complete your Course
Get Certifieda physical version of your officially branded and security-marked Certificate.
About Experienced Data Science Trainer
- Our Data Science Training in Anna Nagar. 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 Anna Nagar from recognized IT organizations.
Data Science Course Reviews
ACTE is the best training institute for Data science and Data Analytics in Anna Nagar. 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.
I have Joined Data Science course in ACTE. This Data Science training in Anna Nagar. It is a good place for knowing and exploring more about Data Science in depth. They teach you from the most basic topics no matter what is your stream. The faculties here are like the best teachers you can get for Data Science training. Thanks to ACTE.
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 Anna Nagar.
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?
- 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
Can I Access the Course Material in Online?
What certification will I receive after course completion?
How Old Is ACTE?
What Will Be The Size Of A Data Science Batch At ACTE?
Will I Be Given Sufficient Practical Training In Data Science?
How Do I Enroll For The Data Science Course At ACTE?
- [BEST & NEW] Kanban Interview Questions and Answers
- 40+ [REAL-TIME] Data Visualization in R Interview Questions and Answers
- CodeIgniter Interview Questions and Answers [ TO GET HIRED ]
- 40+ [REAL-TIME] Laravel Interview Questions and Answers
- Ionic Interview Questions and Answers [BEST & NEW]