Data Science Online Training Overview
This Data Science course will help you told the concepts and tools to utilize during a Data science project. The course includes different key branches that may hold Data science tight along, such as, certified Data Science course, Statistics for Data Science course, Python for Data Science course, Data soul with R course, and a diploma in Data Science.
Data Science Online Training will:
- Learn how to use technology to real-world Data science issues associate degreed gain an in-depth understanding of rising technologies, applied mathematics analysis, and machine techniques.
- This course can make you to skilled in Data Science ideas like Machine Learning, Algorithm, Regression, and Deep Learning.
- Learn Python, R Programming to become the simplest Data science associate within the IT trade.
- Learn how to Deploying clump for analysis segmentation and prediction.
Skills You Will Gain
- R Programmming
- Python, SAS
- Artifical Intelligence
- Deep Learning & Machine Learning
- Statistics, Naive Bayes
- Programming, Neural Networks
- Data Mining, Visualization
Data Science Course Key Features 100% Money Back Guarantee
5 Weeks TrainingFor Become a Expert
Certificate of TrainingFrom Industry Data Science Experts
Beginner FriendlyNo Prior Knowledge Required
Build 3+ ProjectsFor Hands-on Practices
Lifetime AccessTo Self-placed Learning
Placement AssistanceTo Build Your Career
Top Companies Placement
- Annual SalaryHiring Companies
Data Science Course Curriculam
LearnoVita is filled with the best and top MNC trainers +11 years of highly experienced professionals. As all Trainers are working professionals so they are having many live projects , trainers will use these projects during training sessions . Our trainer will give you technical supports and passionate about data and data-driven decision making.
Syllabus of Data Science Course in OMR Download syllabus
- 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.
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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.
Credit Card Fraud Detection
The project consist of data analysis for various parameters of banking dataset and data visualization for finding the probability of occurrence of fraudulent activities.
- Mock interviews by Learnovita give you the platform to prepare, practice and experience the real-life job interview. Familiarizing yourself with the interview environment beforehand in a relaxed and stress-free environment gives you an edge over your peers.
- In our mock interviews will be conducted by industry best Data Science Course in Porur experts with an average experience of 7+ years. So you’re sure to improve your chances of getting hired!
How Learnovita Mock Interview Works?
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Data Science Course Objectives
- Data science has emerged as an attractive career option for freshers as well as experienced professionals. The demand for data engineers is very high in sectors like information technology, telecom, manufacturing, finance and insurance, retail and many more
- Data Science is one of the most highly paid jobs. According to Glassdoor, Data Scientists make an average of $116,100 per year. This makes Data Science a highly lucrative career option. Start Learning Your Advance Data Science Course in Porur
- Career progression opportunities for individuals who become Data Science are excellent
- With IT skills in strong demand, deciding to become a Data Science can open opportunities to progress your career in both the private and public sectors.
- Data Science Salary in worldwide is the most lucrative in all the field of computer, Internet networking industry and More.
- Certainly Yes. Even the recruiters know the knowledge we get in colleges is not enough to do a software job. They will see how confident you are. However they will train you according to their requirement once you get into the company.
- Be confident with your basics that's enough You to get tons of Jobs opportunity by learning Data Science from Data Science Coaching Centers in Porur.
- Deep practical knowledge, Hands-on lab & Data Science Course with placement in Porur.
- Real-time project use cases & scenarios from the various Industries.
- Mock Tests and discussing various questions.
- Data Science Course with Placement in Porur has been actively involved in 100% Job Placement Assistance as a value-added service in the Technical Program. With the backup of an advanced training curriculum and real-time business projects, we have a very consistent and growing Job Placement and Track Record.
- Market entry to various countries and jobs in major corporate.
- Immediate job opportunities after Completion of Advance Data Science Course in Porur.
- Active Coordination with students from the stage of preparing a professional CV/Resume to attend Interviews and securing a Job.
- Preliminary Preparation ensures that our students are able to perform confidently in Interviews even it was their First Interview.
- There are no prerequisites for taking up this training course. If you like mathematics, you can accelerate your learning through this Data Scientist course.
- Mostly Yes, Having Agile Thinking is enough to Understand the Data Science Concepts. Even though The Basic mathematics & Programing Language knowledge is to make Ease to Understand the Concepts Easily.
- Introduction to Data Science and its importance
- Data Science life cycle and data acquisition
- Experimentation, evaluation, and project deployment tools
- Various Machine Learning algorithms
- Predictive analytics and segmentation using clustering
- Fundamentals of Big Data Hadoop
- Roles and responsibilities of a Data Scientist
- Using real-world datasets to deploy recommender systems
- Working on data mining and data manipulation
The Data Science Course is perfect for the below job positions:
- Information Architects and Statisticians
- Developers looking to master Machine Learning and Predictive Analytics
- Big Data, Business Analyst, and Business Intelligence professionals
- Aspirants looking to work as Machine Learning experts, Data Scientists, etc.
- The demand for Data Scientists far exceeds the supply. This is a serious problem in a data-driven world that we are living in today. As a result, most organizations are willing to pay high salaries for professionals with appropriate Data Science skills.
- Data science Course will help you become proficient in Data Science, R programming language, Data Analysis, Big Data, and more. Thus, you can easily accelerate your career in this evolving domain and take it to the next level.
Online Classroom Batches Preferred
(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
No Interest Financing start at ₹ 5000 / month
Exam & Certification
At LearnoVita, You Can Enroll in Either the instructor-led Data Science Online Course, Classroom Training or Online Self-Paced Training.
Data Science Online Training / Class Room:
- Participate and Complete One batch of Data Science Course Course
- Successful completion and evaluation of any one of the given projects
Data Science Online Self-learning:
- Complete 85% of the Data Science Certification Training
- Successful completion and evaluation of any one of the given projects
These are the Different Kinds of Certification levels that was Structured under the Data Science Certification Path.
- Certified Analytics Professional (CAP)
- Cloudera Certified Associate: Data Analyst
- Cloudera Certified Professional: CCP Data Engineer
- Data Science Council of America (DASCA) Senior Data Scientist (SDS)
- Data Science Council of America (DASCA) Principle Data Scientist (PDS)
- Dell EMC Data Science Track
- Google Certified Professional Data Engineer
- Google Data and Machine Learning
- IBM Data Science Professional Certificate
- Microsoft MCSE: Data Management and Analytics
- Microsoft Certified Azure Data Scientist Associate
- Open Certified Data Scientist (Open CDS)
- SAS Certified Advanced Analytics Professional
- SAS Certified Big Data Professional
- SAS Certified Data Scientist
- Learn About the Certification Paths.
- Write Code Daily This will help you develop Coding Reading and Writing ability.
- Refer and Read Recommended Books Depending on Which Exam you are Going to Take up.
- Join LernoVita Data Science Certification Training in Porur That Gives you a High Chance to interact with your Subject Expert Instructors and fellow Aspirants Preparing for Certifications.
- Solve Sample Tests that would help you to Increase the Speed needed for attempting the exam and also helps for Agile Thinking.
Pranav SrinivasSoftware Testing, Capgemini
Data Science Course FAQ's
- LearnoVita Best Data Science Course in Porur will assist the job seekers to Seek, Connect & Succeed and delight the employers with the perfect candidates.
- On Successfully Completing a Career Course from LearnoVita Best Data Science Course in Porur, you Could be Eligible for Job Placement Assistance.
- 100% Placement Assistance* - We have strong relationship with over 650+ Top MNCs, When a student completes his/ her course successfully, LearnoVita Placement Cell helps him/ her interview with Major Companies like Oracle, HP, Wipro, Accenture, Google, IBM, Tech Mahindra, Amazon, CTS, TCS, HCL, Infosys, MindTree and MPhasis etc...
- LearnoVita is the Legend in offering placement to the students. Please visit our Placed Students's List on our website.
- More than 5400+ students placed in last year in India & Globally.
- LearnoVita is the Best Data Science Course Institute in Porur Offers 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's Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
- LearnoVita Certification is Accredited by all major Global Companies around the World.
- LearnoVita is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of Data Science and National Institute of Education (nie) Singapore
- Also, LearnoVita Technical Experts Help's People Who Want to Clear the National Authorized Certificate in Specialized IT Domain.
- LearnoVita is offering you the most updated Data Science certification training in Porur, relevant, and high-value real-world projects as part of the training program.
- All training comes with multiple projects that thoroughly test your skills, learning, and practical knowledge, making you completely industry-ready.
- You will work on highly exciting projects in the domains of high technology, ecommerce, marketing, sales, networking, banking, insurance, etc.
- After completing the projects successfully, your skills will be equal to 6 months of rigorous industry experience.
- We will reschedule the Data Science classes in Porur as per your convenience within the stipulated course duration with all such possibilities.
- View the class presentation and recordings that are available for online viewing.
- You can attend the missed session, in any other live batch.