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Data Science Training in Trivandrum

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Play a design role and participate in IT companies.

  • This course examines the essential tools and concepts of data science, including machine learning, statistical analysis, and working with data at scale.
  • We will discuss the various roles and skills that are involved in the data science process in the following sections. Later in the course, you'll learn how to get data from various sources, such as web APIs and internet scraped pages.
  • Get to know how to use tools like R, Python, the command line, and spreadsheets for working with data.
  • A powerful method for data analysis will be discussed as well. A number of techniques will be covered in this course for planning, performing, and presenting data science projects. Using these tools and techniques will help you get started in data science and make your data use more efficient.
  • You will be provided with a comprehensive toolkit for a data science career throughout the course. We will provide an overview of different careers in the field, including Product Analyst, Data Engineer, Data Scientist, and many more.
  • You will be able to take full advantage of any options available when you are aware of them. Among other topics, the course covers probability, statistics, machine learning, product metrics, A/B testing, and market analysis.
  • There will be contributions from many world-renowned technology companies, including Amazon, Square, Facebook, Google, Microsoft, AirBnB, and more!
  • Students will be provided with detailed explanations and solutions to each question in the course. The program can also help you to prepare for exams and act as a reference while working.
  • To succeed in the interview, you need to be familiar with the following topics.
  • Using this curriculum, students will gain a better understanding of the subject. By going through our program, students can learn how to prepare for interviews and obtain employment at reputable companies.
  • 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!
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This is How ACTE Students Prepare for Better Jobs

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Course Objectives

Let's always be things straight: to even get a job in data science, you should not need a data science credential. Your data preparation should be selected based on its skills rather than on a credential because hiring managers are not really interested in any certification for data sciences.

While it took 2 to3 years mostly to teach you all of this in undergraduates and Masters courses at educational institutions, many claims that you can acquire them by spending 6 to 7 hours a day in just six months.

The various edges of Data Science are as follows: It's in Demand. Data Science is greatly in demand. The abundance of Positions. An extremely Paid Career. Data Science is flexible. Data Science Makes knowledge higher. Data Scientists are extremely Prestigious. No additional Boring Tasks. Data Science Makes merchandise Smarter.

  • One of the highest-paid workers is the data center.
  • Data scientists earn an average of ₹698,412 a year, and according to Glassdoor.
  • Data Science is therefore a very attractive career choice.
AWS jobs you'll be able to get with AWS certification Operational Support Engineer:
  • Identity what you need to know.
  • Get Python in comfort.
  • Learn Pandas Statistical Analysis, handling, and viewing.
  • Learn scientist-learn machine learning.
  • Comprise more breadth of machine learning.
  • Continue to study and practice.
  • Data scientists are responsible for doing what data engineers can do in certain organizations.
  • Although data scientists are not capable of being data engineers, they may obtain the know-how.
  • But in the other extreme, if data engineers start to do data science, it is much less popular.

Based on the topic knowledge of statistics, machine learning, and programming, students become specialists in implementing Data Science methodologies within the practical world. Students from different streams, like business studies, also are eligible for relevant courses in Data Science. Data science groups have groups from diverse backgrounds like chemical engineering, physics, economics, statistics, arithmetic, research, engineering science, etc. You may realize several knowledge scientists with an academic degree in statistics and machine learning however it's not a demand to learn data science.

Is Data Analyst and Data Scientist the same?

Simply put, a data analyst is smart out of existing data, whereas a data somebody works on new ways in which of capturing and analyzing data to be used by the analysts. If you like numbers and statistics in addition to programming, either path may well be suited to your career goals. Each works with knowledge, however, the key distinction is what they are doing with this knowledge. Data analysts sift through knowledge and obtain to spot trends. Data scientists are execs at decoding knowledge, however additionally tend to possess cryptography and mathematical modeling experience.

Can freshers get a job in Data Science Certification Training Course?

Entry-level knowledge somebody salaries are as motivating because of the job itself. If you'll crack the Amazon data science situation or Google data science situation, the expertise you can gather here will offer a grip to your career, then there would be no wanting back. Any novice will become an information somebody the sole would like is to learn the tricks of the business and needed skills.

What is the main purpose of the Data Science Certification Training Course?

The purpose of Data Science is to create the means for obtaining business-focused penetrations from data. This needs an understanding of however worth and information flows during a business, and also the ability to use that understanding to spot business opportunities. It's developing technology and there's a large necessity for data Analysts and knowledge somebody within the current mechanical world.

What courses should I take for Data Science Certification Training Course?

Once you're practiced as a computer user, take courses on the following: Algorithm style and Analysis. Scientific Computation. Probability and applied mathematics Modeling for engineering science. Software Engineering. Database Systems. Introduction to AI. Machine Learning. Image process and Analysis.

What skills do you need for Data Analysis?

Essential skills for a data analyst high level of mathematical ability. The ability to analyze, model, and interpret knowledge. Problem-solving skills. An organized and logical approach. The ability to set up work and meet deadlines. Accuracy and a focus on detail.

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Overview of Data Science Training in Trivandrum

In this data science course in Trivandrum, you will learn about the analytics and data science paradigm, data exploration, data visualisation using various tools like Tableau, SQL, and MS Excel. As a result, our curriculum is based on current market requirements and covers the entire data science lifecycle principles from data collection to data extraction to data cleaning to data exploration to data visualisation to data transformation to data integration to data mining. You will learn data mining, data management, exploration, and carry out numerous industry-relevant projects in this data science course in Trivandrum, which has been created by a data science specialist. Enroll & Get Certified now!

Additional Info

Career Prospects of Data Science:

Data Science is currently thought of one amongst the foremost financially moneymaking positions within the trade. With varied openings spanning all fields, knowledge science jobs solely reveal indications of progress. Once a lot of and a lot of organizations adopt knowledge science, companies square measure recruiting multitudes of information scientists. However, the demand-supply gap for knowledge science jobs and candidates is merely rising, despite India being a front-runner in technical education and analysis studies. Seventy % of the task postings during this sector is for knowledge scientists with but 5 years of labor expertise at this stage within the analytics trade.

Data science Certification Training and Exam and path

1. holler EMC well-tried skilled Certification Program:- Basically, holler EMC offers an information science associate certification. That guarantees a active, professional approach. That describes because the “industry’s most comprehensive learning and certification program.” As presently as you pass this knowledge human certification, you’re thought of “Proven skilled,”.

2. Certified Analytics skilled:- Generally, CAP offers a vendor-neutral knowledge human certification. That shows recruiters and managers that you simply aren’t biased to specific software package. Also, it shows that you simply have a broad vary of information in your field. It helps you to balance out yours a lot of specific, well-honed skill sets.

3. SAS Academy for knowledge Science:- As SAS Academy for knowledge Science includes 3 programs. One that focuses on huge knowledge skills; Another that focuses on knowledge analytics skills, and A third program that has each knowledge analytics and large knowledge skills. Moreover, it’s an excellent thanks to get exposure and knowledge victimization knowledge Science Tools to induce knowledge human certification.

4. Microsoft Certified Solutions knowledgeable (MCSE):- As MCSE certifications cowl a good style of IT specialties and skills. As skills square measure supported knowledge science. Also, for its knowledge human certification, Microsoft offers 2 courses; one that focuses on business applications, and another that focuses on knowledge management and analytics. But, it’s necessary to possess previous certification below the MCSE for every course. Thus, it makes it positive that you simply have checked the necessities initially.

5. Cloud era Certified Associate (CCA):- Basically, this communication indicates your basic information as a developer. And conjointly as associate administrator of Cloud era’s enterprise software package. Once you've got past this communicating.

Industry Trends of Data Science:

The presence knowledge|of knowledge|of information} in each field that you simply will think about is what seems to be a reason why organizations square measure showing interest in data science. Also, the very fact that knowledge can still be associate integral a part of our lives until eternity serves to be yet one more driver of knowledge science. That said, it’s very necessary to remain updated with the most well liked knowledge science trends that would serve to be a blessing to grow your business. Here square measure the highest ten knowledge science trends for this decade.

Predictive analysis:- For a business to prosper, it's vital to understand what the long run may seem like. This is often specifically wherever prophetical analysis comes into play. Organizations consider their customers to an oversized extent. Hence, having the ability to grasp their behaviors helps in creating higher choices ahead. This method is one in every of the best to return up with the most effective methods to focus on the purchasers that’d aid in retentive the older ones and additionally get newer customers.

Machine learning:- Over the years, we've seen what proportion automation has reworked the planet. this is often why machine learning has gained importance like né'er before. the approaching years can see a lot of automation and thus the increase within the variety of organizations adopting machine learning can surpass one’s imagination of course.

IoT:- Gone square measure the times once IoT was thought-about to be one thing that may have restricted applications. Today, we have a tendency to live in an exceedingly world wherever our smartphones have the power to manage appliances like TV, AC, etc. All of this is often potential due to IoT. Google Assistant is yet one more exceptional innovation within the space of IoT. Thus, corporations searching for ways that to take a position during this technology come back as no massive surprise. This merely throws light-weight on however chop-chop the IoT trade would grow within the days ahead.

Blockchain:- Needless to mention, cryptocurrencies like Bitcoin, Litecoin, etc. became to speak the planet. All of those currencies use blockchain technology. With the planet showing keen interest during this field, it for certain stands an extensive implementation within the returning time.

Edge computing:- Edge computing is thought for quicker process of data, and it additionally boasts of reducing latency, price and traffic. it's exclusively due to these options that the organizations don't seem to be willing to sideline this feature. With this computing in situ, handling time period applications couldn’t have gotten any higher. the approaching years might see a lot of a substantial shift from ancient strategies thereto of edge computing.

DataOps:- Lets’ face the fact — the information pipeline has become a lot of complicated and so needs even a lot of integration and governance tools. DataOps to our rescue it is! Tasks right from assortment to preparation to analysis, testing automation, implementing machine-controlled testing, delivery for providing increased knowledge quality and analysis square measure all lined. This trend can continue for the years to return.

Artificial Intelligence:- Be it little enterprise or a technical school big, all of them have relied on AI in a method or the opposite. All those complicated tasks aren't any longer a priority for we have a tendency to currently will consider AI for a similar. Also, the reduction in errors is yet one more sturdy reason to why AI stands apart. currently, that we’ve relied on AI such a lot, there’s no returning.

Data mental image:- This is one in every of those distinguished trends that we will trust with. this is often as a result of the organizations square measure moving their typical knowledge warehouses to the cloud.

Better user expertise:- The extent to that user expertise is given importance to talks volume regarding the success of the corporate. this is often why corporations square measure feat no stone right-side-up in providing the most effective potential user expertise — be it within the style of chatbots, personal help, or AI-driven tools for that matter.

Data governance:- This is yet one more space that’s gaining a great deal of importance. varied corporations out there square measure still troubled to adjust to the foundations and rules. it's vital to not simply adjust to these however additionally to grasp the impact of a similar on the current and future operations. knowledge scientists United Nations agency have sound information regarding all of this is often the necessity of the hour.

Top framework or technologies and major tool in Data Science

1. Tensorflow:- TensorFlow is associate degree end-to-end Machine Learning platform that includes comprehensive, versatile framework of tools and libraries together with community resources, serving to you build Machine Learning supercharged applications simply. TensorFlow was initial created by Google Brain Team and to the present day remains ASCII text file.

2. Scikit-learn:- Scikit-learn is associate degree ASCII text file Machine Learning library to be used in Python programming language, that includes numerous classification, agglomeration and regression algorithms. It's designed to interoperate with numerical and scientific libraries like NumPy and SciPy, each developed and employed in Python.

3. Keras:- Keras could be an in style ASCII text file computer code library that's capable of running atop alternative libraries like TensorFlow, Theano and CNTK. With tons of information, you'll dabble in Deep Learning and AI over this framework.

4. Pandas:- A information manipulation and analysis language written in python and for python supply data structures and operations for manipulating NumPy based mostly tables and statistic. It's wont to normalize incomplete and mussy information with options of shaping, slicing, dicing and merging datasets.

5. Spark Mlib:- A library with an in depth support for Java, Scala, Python and R, this framework may be used on Hadoop, Apache Mesos, Kubernetes, over cloud services handling multiple information sources.

6. Pytorch:- A Facebook developed framework, PyTorch is associate degree AI-specific framework for Deep Learning. The PyTorch library permits dynamic updates of graphs permitting on the fly changes to the design.

7. Matplotlib:- Based on MATLAB, Matplotlib could be a plotting library for Python, with in depth support for made image and dynamic charts. It's a numerical extension of the NumPy library to get beautiful graphs and plots. The default image library in each information science project in Python, Matplotlib helps you produce interactive visualizations together with histograms, 3Dplots, scatter plots, image plots, bar charts and lots of additional

8. Numpy:- Numpy, associate degree ASCII text file library, brings within the machine power of C to Python, with powerful information structures for number-crunching applications like Quantum Computing, applied math computing, signal process, image process, graphs and networks, urbanology processes, psychological science and additional.

9. Seaborn:- An ASCII text file Python library, Seaborn could be an image package supported Matplotlib. You get to figure with high-level interfaces for manufacturing made and enticing applied math graphs.

10. The Ano:- Theano ensures that computations as expressed expeditiously on either CPU or GPU architectures.

Future in Data Science developer and trending

Data Science has tremendous applications not simply restricted to 1 field. Its application's area unit distributed across varied sectors. Let’s mention few major future developments in knowledge Science:

Automobile trade:- industry saw a significant shift within the previous couple of years and still within the development stage. Self Driving cars, Autopilot flying cars, fastened Destination Cabs, Automatic transport, and varied different applications. These thing's area unit potential within the coming back future. However, such developments need an oversized cluster of enthusiastic individuals to not simply build code however additionally think about, additional blessings that knowledge Science will bring that earlier wasn't there. therefore, industry could be a new powerhouse to jobs and opportunities in knowledge Science.

IT:- most of the people confuse knowledge Science with IT and its services. however, the very fact is knowledge Science is pure mathematical capabilities combined with the wonders of code Engineering to developing what we tend to decision these days — Machine Learning. IT sector has shown huge growth within the world’s gross domestic product. However, once we mention the IT sector as an entire knowledge Science is currently changing into a key facet of any victorious data-driven company. When we mention whether introducing new changes to the website or existing app can bring new customers or can lose its customers. Then, knowledge Science becomes an awfully vital half to spot what impact can new changes have. Knowledge Science has varied different applications within the IT sector, together with Network Safety additionally.

Healthcare:- the most important application or marvel of information Science is in tending. With the provision of huge datasets of patients, we are able to use that to create an information Science approach to spot the diseases at terribly early stages. Tending is one among the most important sectors for providing opportunities for the skilled World Health Organization will use their medical experience with knowledge Science and supply immediate facilitate to the suffering patients. Tending provides varied different opportunities in addition by combining an information Science approach to spot needed organs and their availableness within the region of the planet.

Army and Weapons:- each Nation has engineered stronger from a stronger army strength. It’s a wise man’s sayings that power isn’t one thing that ought to be used for creating humankind slaves. It should be wont to free humankind from any threats. Justifying {the fact|the terrible fact|the actual fact} knowledge Science will facilitate in building varied automatic solutions to spot any attack in a very early stage serving to prevent the cause. Aside from that knowledge Science will facilitate in building automatic weapons that may be good enough to spot once to fireplace and once to not.

Power and Energy:- With the rise in population the demand for energy has exaggerated exponentially. That needs energy to be handled to such tier that while not exhausting the present Natural Resources we tend to should be capable to produce energy demands consummated. Knowledge Science will facilitate in predicting the consequences of atomic power sources. Data Science will predict the safest potential. Knowledge Science will facilitate in building AI bots which will simply handle huge power sources.

Banking and Finance:- {when we tend to|once we|after we} mention the safety of our cash we forever think about the bank. however, with the introduction of on-line transactions, fraud had exaggerated in addition. Banking and monetary knowledge beside security need stable systems to spot fraud activities before they'll really cause harm. Another facet of information Science within the Banking and Finance sector is managing the money effectively to own invested with within the right places supported knowledge Science predictions for best results. The biggest innovation of your time is Cryptocurrency. With cryptocurrency within the market, the stress for managing knowledge on-line became a significant challenge. Knowledge Science offers varied techniques to spot an identical cluster of individuals and providing them the most effective potential security from fraud activities in addition.

Data Science Training Key Features

1. information Exploration:- It is the foremost vital step, as this step consumes the foremost quantity of your time. Around seventy per cent of the time is spent on information exploration. The most ingredient for information science is information, thus after we get information, it's rarely that information is during a correct structured type. There's a great deal of noise gift within the information. The noise here suggests that a great deal of unwanted information that's not needed. thus, what we tend to|can we|will we} knock off this step? This step involves sampling and transformation of knowledge within which we check the observations (rows) and options (columns) and take away the noise by exploitation applied math ways. This step is additionally accustomed check the connection among varied features(columns) within the information set; by the connection, we have a tendency to mean whether the features(columns) square measure enthusiastic about different|one another} or freelance of every other, whether there square measure missing values information or not. thus, primarily, the info is remodeled and readied for additional use. thus, this is often one in every of the foremost long steps.

2. Modeling:- So, by now, our information is ready and prepared to travel. This is often the second step, wherever we have a tendency to truly use Machine Learning algorithms. Here we have a tendency to truly work the info into the model. The choice of a model depends on the sort of knowledge we've got and also the business demand. As an example, the model choice for recommending a piece to a client are going to be totally different from the model needed for predicting the amount of articles that may be sold-out on a specific day. Once the model is determined, we have a tendency to work the info into the model.

3. Testing the Model:- It is succeeding step and extremely vital regarding the performance of the model. The model is checked with test information to ascertain the model’s accuracy and alternative characteristics and build the specified changes within the model to induce the required result. Just in case we have a tendency to don't get the required accuracy, we are able to once more head to step 2(modelling), choose a unique model, so repeat constant step three and select the model which provides the most effective result as per the business demand.

4. Deploying Models:- Once we have a tendency to get the required result by correct testing as per the business necessities, we have a tendency to end the model, which provides America the most effective result as per testing results, and deploys the model within the production surroundings.

Pay Scale of Data Science Developer

The average information scientists wage is 698,412. Associate degree entry-level information person will earn around 500,000 once a year with but one year of expertise. Early level information scientists with one to four years expertise get around 610,811 once a year.

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Key Features

ACTE Trivandrum 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

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.
 

Curriculum

Syllabus of Data Science Course in Trivandrum
Module 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.
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 Projects

Project 1
Image Caption Generator Project in Python

The objective of our project is to learn the concepts of a CNN and LSTM model and build a working model of Image caption generator by implementing CNN with LSTM.

Project 2
Credit Card Fraud Detection Project

The objectives of credit card fraud detection are to reduce losses due to payment fraud for both merchants and issuing banks and increase revenue opportunities for merchants.

Project 3
Movie Recommendation System

Recommender systems are information filtering tools that aspire to predict the rating for users and items, predominantly from big data.

Project 4
Customer Segmentation Project

Customer segmentation is the division of customers into groups based on specific customer data. The aim of segmentation is to increase sales.

Our Engaging Placement Partners

ACTE Trivandrum for affirmation and Guaranteed Situations. Our Work Situated classes are educated by experienced confirmed experts with broad certifiable experience. All our Best around down to earth than hypothesis model.
  • Begin with the Data Science Training undertaking and assessment everything concerning the program.
  • After finish of half Data Science Training informative class content, we will put together the party calls to understudies and set them up to f2f correspondence.
  • We offers a different appplicants entrance for technique with free acknowledgment to look at material.
  • We have a submitted methodology support pack wing that help understudies in getting situation as indicated by their necessities.
  • We are connected with top affiliations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM, and so on it make us fit to put our understudies in top MNCs across the globe.
  • Our Data Science Training in Trivandrum is offered with plan help through keep making capacities, business improvement counsel, correspondence progression, work glancing through data, and character headway preparing that help the understudies with getting updated capacities for getting the gatherings liberated from top associations with no issue.

Get Certified By MCSE: Data Management and Analytics & Industry Recognized ACTE Certificate

Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees. Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

Get Certified

a physical version of your officially branded and security-marked Certificate.

Get Certified

About Skillful Data Science Instructor

  • Our Data Science Training in Trivandrum. Our guides offer rigid freedom to the understudies, to investigate the subject and learn reliant upon relentless models. Our coaches help the enemies in completing their endeavors and amazingly set them up for requests questions and answers. Contenders are permitted to address any requesting at whatever point.
  • To test learner knowledge on Data science training, learner will be depended upon to work on two industry-based exercises that evaluate titanic unending use cases. This will other than ensure dynamic Best Data Science Training and Course considerations.
  • Building up specialists by basically experienced prepared experts in realistic scenario.
  • Well related with selecting HRs in as a rule affiliations and guides applicants about placement career.
  • Special thought is given to each understudy to get benefitted with the approach and placed in Top Mncs.
  • Courses are passed on by capable and especially qualified coach, with wide consolidation with their different endeavors.
  • As all our Trainers are Data Science Training domain working professionals so they are having many live projects, trainers will use these projects during training sessions.

Data Science Course Reviews

Our ACTE Trivandrum Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.

Nandhini

Student

ACTE is the best training institute for Data science and Data Analytics in BTM Layout. The trainers are well experienced and the methodology of teaching is top notch. They provide practicals along with theoretical sessions for complete understanding of the concepts. They even provide placement assistance after course completion as well.

Sheshaiya

Software Engineer

I joined here for Data Science course in Triandrum. The training here is very useful and helpful. Staff are very friendly. Placement opportunities are also very good. It is a good environment for people. I really recommend ACTE to everyone especially for those who need good start for IT career.

Ebenazar

Best DATA SCIENCE training institute in Tambaram with Realtime client projects and dedicated support team. I have taken Data science training on this January and completely happy with their teachings, projects and job support after the course completion. It's a One stop destination for your data science And AI training in BTM Layout.

Illakiya

Student

ACTE for your career switch to Data Science..They have well experienced Trainers in ACTE who can make you industry ready. Curriculum is quite unique and includes current industry needs. They give very good job assistance also.

Tharani

Software Engineer

Its a good institute for Data Science in Porur. The teaching staff is good, they give us day wise assignments which helped me to hands on algorithms of machine learning and also provide us the backup classes. The access they provide is very helpful to listen the classes repeatedly. They provide good placement assistance. Thanks social ACTE team for your support and guidance.

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Data Science Course FAQs

Looking for better Discount Price?

Call now: +91 93833 99991 and know the exciting offers available for you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
ACTE
    • Gives
Certificate
    • For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Data Science 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 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
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 batch to 5 or 6 members
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.
You can contact our support number at +91 93800 99996 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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