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In this Data Science training course in Houston helps you master Data Analytics, Business Analytics, Data Modeling, Machine Learning algorithms, K-Means Clustering, Naïve Bayes, etc. This training will help you learn R statistical computing, building recommendation engine for e-commerce, recommending movies and deploy market basket analysis in the retail sector. Get the best online data science training in Houston from top data scientists.
Intellipaat offers a definitive Data Scientist training in Houston, that lets you have a complete learning experience in data acquisition, cleansing, aggregation and analysis. You will also be applying statistical methods and Machine Learning algorithms, deploying recommender systems using Apache Mahout, understanding R programming and more through this training.
Intellipaat is a premier online training institute which helps you master concepts like
Intellipaat’s online training course is exclusively designed by industry experts for
There are no particular prerequisites for this training course. If you love mathematics, it is helpful.
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 training online will help you become proficient in Data Science, R programming, Data Analysis, Big Data, and more. Thus, you can easily accelerate your career in this evolving domain and take it to the next level.
Houston in Texas is a top destination for businesses ranging from oil and gas, high technology, automobile, manufacturing, space research and aviation to many others. All these industries are extensively deploying Data Science tools and techniques for getting more business insights. Hence, there are wide-ranging jobs in this domain in the city, Texas, in the United States.
Top companies that hire Data Scientists are:
According to Glassdoor, the average income of a Data Scientist in Houston is US$122,801 per year.
In this course, we have included real-world industry-based projects, which help you gain hands-on experience in the field and prepare you for challenging roles.
| Industry | Project Name | Objective |
| BFSI | Fraud Detection in Banking System | Deploying Data Science to detect fraudulent activities and take remedial actions |
| Entertainment | Movie Recommendation Engine | Building a movie recommendation engine, based on user interests |
| E-commerce | Making Sense of Customer Buying Patterns | Deploying target selling to customers |
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1.1 What is Data Science?
1.2 Significance of Data Science in today’s data-driven world, its applications of, , lifecycle, and its components
1.3 Introduction to R programming and RStudio
Hands-on Exercise:
1. Installation of RStudio
2. Implementing simple mathematical operations and logic using R operators, loops, if statements, and switch cases
2.1 Introduction to data exploration
2.2 Importing and exporting data to/from external sources
2.3 What are data exploratory analysis and data importing?
2.4 DataFrames, working with them, accessing individual elements, vectors, factors, operators, in-built functions, conditional and looping statements, user-defined functions, and data types
Hands-on Exercise:
1. Accessing individual elements of customer churn data
2. Modifying and extracting results from the dataset using user-defined functions in R
3.1 Need for data manipulation
3.2 Introduction to the dplyr package
3.3 Selecting one or more columns with select(), filtering records on the basis of a condition with filter(), adding new columns with mutate(), sampling, and counting
3.4 Combining different functions with the pipe operator and implementing SQL-like operations with sqldf
Hands-on Exercise:
1. Implementing dplyr
2. Performing various operations for manipulating data and storing it
4.1 Introduction to visualization
4.2 Different types of graphs, the grammar of graphics, the ggplot2 package, categorical distribution with geom_bar(), numerical distribution with geom_hist(), building frequency polygons with geom_freqpoly(), and making a scatterplot with geom_pont()
4.3 Multivariate analysis with geom_boxplot
4.4 Univariate analysis with a barplot, a histogram and a density plot, and multivariate distribution
4.5 Creating barplots for categorical variables using geom_bar(), and adding themes with the theme() layer
4.6 Visualization with plotly, frequency plots with geom_freqpoly(), multivariate distribution with scatter plots and smooth lines, continuous distribution vs categorical distribution with box-plots, and sub grouping plots
4.7 Working with co-ordinates and themes to make graphs more presentable, understanding plotly and various plots, and visualization with ggvis
4.8 Geographic visualization with ggmap() and building web applications with shinyR
Hands-on Exercise:
1. Creating data visualization to understand the customer churn ratio using ggplot2 charts
2. Using plotly for importing and analyzing data
3. Visualizing tenure, monthly charges, total charges, and other individual columns using a scatter plot
5.1 Why do we need statistics?
5.2 Categories of statistics, statistical terminology, types of data, measures of central tendency, and measures of spread
5.3 Correlation and covariance, standardization and normalization, probability and the types, hypothesis testing, chi-square testing, ANOVA, normal distribution, and binary distribution
Hands-on Exercise:
1. Building a statistical analysis model that uses quantification, representations, and experimental data
2. Reviewing, analyzing, and drawing conclusions from the data
6.1 Introduction to Machine Learning
6.2 Introduction to linear regression, predictive modeling, simple linear regression vs multiple linear regression, concepts, formulas, assumptions, and residuals in Linear Regression, and building a simple linear model
6.3 Predicting results and finding the p-value and an introduction to logistic regression
6.4 Comparing linear regression with logistics regression and bivariate logistic regression with multivariate logistic regression
6.5 Confusion matrix the accuracy of a model, understanding the fit of the model, threshold evaluation with ROCR, and using qqnorm() and qqline()
6.6 Understanding the summary results with null hypothesis, F-statistic, and
building linear models with multiple independent variables
Hands-on Exercise:
1. Modeling the relationship within data using linear predictor functions
2. Implementing linear and logistics regression in R by building a model with ‘tenure’ as the dependent variable
7.1 Introduction to logistic regression
7.2 Logistic regression concepts, linear vs logistic regression, and math behind logistic regression
7.3 Detailed formulas, logit function and odds, bivariate logistic regression, and Poisson regression
7.4 Building a simple binomial model and predicting the result, making a confusion matrix for evaluating the accuracy, true positive rate, false positive rate, and threshold evaluation with ROCR
7.5 Finding out the right threshold by building the ROC plot, cross validation, multivariate logistic regression, and building logistic models with multiple independent variables
7.6 Real-life applications of logistic regression
Hands-on Exercise:
1. Implementing predictive analytics by describing data
2. Explaining the relationship between one dependent binary variable and one or more binary variables
3. Using glm() to build a model, with ‘Churn’ as the dependent variable
8.1 What is classification? Different classification techniques
8.2 Introduction to decision trees
8.3 Algorithm for decision tree induction and building a decision tree in R
8.4 Confusion matrix and regression trees vs classification trees
8.5 Introduction to bagging
8.6 Random forest and implementing it in R
8.7 What is Naive Bayes? Computing probabilities
8.8 Understanding the concepts of Impurity function, Entropy, Gini index, and Information gain for the right split of node
8.9 Overfitting, pruning, pre-pruning, post-pruning, and cost-complexity pruning, pruning a decision tree and predicting values, finding out the right number of trees, and evaluating performance metrics
Hands-on Exercise:
1. Implementing random forest for both regression and classification problems
2. Building a tree, pruning it using ‘churn’ as the dependent variable, and building a random forest with the right number of trees
3. Using ROCR for performance metrics
9.1 What is Clustering? Its use cases
9.2 what is k-means clustering? What is canopy clustering?
9.3 What is hierarchical clustering?
9.4 Introduction to unsupervised learning
9.5 Feature extraction, clustering algorithms, and the k-means clustering algorithm
9.6 Theoretical aspects of k-means, k-means process flow, k-means in R, implementing k-means, and finding out the right number of clusters using a scree plot
9.7 Dendograms, understanding hierarchical clustering, and implementing it in R
9.8 Explanation of Principal Component Analysis (PCA) in detail and implementing PCA in R
Hands-on Exercise:
1. Deploying unsupervised learning with R to achieve clustering and dimensionality reduction
2. K-means clustering for visualizing and interpreting results for the customer churn data
10.1 Introduction to association rule mining and MBA
10.2 Measures of association rule mining: Support, confidence, lift, and apriori algorithm, and implementing them in R
10.3 Introduction to recommendation engines
10.4 User-based collaborative filtering and item-based collaborative filtering, and implementing a recommendation engine in R
10.5 Recommendation engine use cases
Hands-on Exercise:
1. Deploying association analysis as a rule-based Machine Learning method
2. Identifying strong rules discovered in databases with measures based on interesting discoveries
11.1 Introducing Artificial Intelligence and Deep Learning
11.2 What is an artificial neural network? TensorFlow: The computational framework for building AI models
11.3 Fundamentals of building ANN using TensorFlow and working with TensorFlow in R
12.1 What is a time series? The techniques, applications, and components of time series
12.2 Moving average, smoothing techniques, and exponential smoothing
12.3 Univariate time series models and multivariate time series analysis
12.4 ARIMA model
12.5 Time series in R, sentiment analysis in R (Twitter sentiment analysis), and text analysis
Hands-on Exercise:
1. Analyzing time series data
2. Analyzing the sequence of measurements that follow a non-random order to identify the nature of phenomenon and forecast the future values in the series
13.1 Introduction to Support Vector Machine (SVM)
13.2 Data classification using SVM
13.3 SVM algorithms using separable and inseparable cases
13.4 Linear SVM for identifying margin hyperplane
14.1 What is the Bayes theorem?
14.2 What is Naïve Bayes Classifier?
14.3 Classification Workflow
14.4 How Naive Bayes classifier works and classifier building in Scikit-Learn
14.5 Building a probabilistic classification model using Naïve Bayes and the zero probability problem
15.1 Introduction to the concepts of text mining
15.2 Text mining use cases and understanding and manipulating the text with ‘tm’ and ‘stringR’
15.3 Text mining algorithms and the quantification of the text
15.4 TF-IDF and after TF-IDF
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Market Basket Analysis
This is an inventory management project where you will find the trends in the data that will help the company to increase sales. In this project, you will be implementing association rule mining, data extraction, and data manipulation for the Market Basket Analysis.
Credit Card Fraud Detection
The project consists of data analysis for various parameters of banking dataset. You will be using a V7 predictor, V4 predictor for analysis, and data visualization for finding the probability of occurrence of fraudulent activities.
Loan Approval Prediction
In this project, you will use the banking dataset for data analysis, data cleaning, data preprocessing, and data visualization. You will implement algorithms such as Principal Component Analysis and Naive Bayes after data analysis to predict the approval rate of a loan using various parameters.
Netflix Recommendation System
Implement exploratory data analysis, data manipulation, and visualization to understand and find the trends in the Netflix dataset. You will use various Machine Learning algorithms such as association rule mining, classification algorithms, and many more to create movie recommendation systems for viewers using Netflix dataset.
Case Study 1: Introduction to R Programming
In this project, you need to work with several operators involved in R programming including relational operators, arithmetic operators, and logical operators for various organizational needs.
Case Study 2: Solving Customer Churn Using Data Exploration
Use data exploration in order to understand what needs to be done to make reductions in customer churn. In this project, you will be required to extract individual columns, use loops to work on repetitive operations, and create and implement filters for data manipulation.
Case Study 3: Creating Data Structures in R
Implement numerous data structures for numerous possible scenarios. This project requires you to create and use vectors. Further, you need to build and use metrics, utilize arrays for storing those metrics, and have knowledge of lists.
Case Study 4: Implementing SVD in R
Utilize the dataset of MovieLens to analyze and understand single value decomposition and its use in R programming. Further, in this project, you must build custom recommended movie sets for all users, develop a collaborative filtering model based on the users, and for a movie recommendation, you must create realRatingMatrix.
Case Study 5: Time Series Analysis
This project required you to perform TSA and understand ARIMA and its concepts with respect to a given scenario. Here, you will use the R programming language, ARIMA model, time series analysis, and data visualization. So, you must understand how to build an ARIMA model and fit it, find optimal parameters by plotting PACF charts, and perform various analyses to predict values.
The entire Data Science course content is designed by industry professionals for you to get the best jobs in top MNCs. As part of Data Science online courses, you will be working on various projects and assignments that have immense implications in real-world scenarios. They will help you fast-track your career effortlessly.
At the end of this Data Science online training program, there will be quizzes that perfectly reflect the type of questions asked in the respective certification exams.They will help you score better.
Intellipaat’s course completion certificate will be awarded to you when you complete the project work and score at least 60 percent marks in the quiz. This certification is well recognized in the top 80+ MNCs,such as Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Standard Chartered, TCS, Genpact, etc.
Swetha Pandit
Intellipaat’s Data scientist certification training in Houston online are well structured and taught by recognized professionals. They help one learn Data Science fast. I have found their videos to be of excellent quality. Thanks a lot!
Excellent course, I found Intellipaat's training team to be talented in their respective domain. My training was very good as it helped me in upgrading my skills, which proved to be a turning point in my career. Intellipaat's mentor was well-experienced and his teaching method was really great. This online course helped me to get deep understanding of the technology. Moreover, the excercise and projects provided as a part of the course made me to get hands-on experience. Besides, the online support team was very helpful and offered their assistance as and when I needed via calls and emails.
I had taken the Data Science master’s program, which is a combo of SAS, R, and Apache Mahout. Since there are so many technologies involved training courses, getting our query resolved at the right time becomes the most important aspect. But with Intellipaat, there was no such problem as all my queries were resolved in less than 24 hours.
I was searching for various programs of Data Science, and I landed on Intellipaat’s course page. It was really good in terms of content. The sample video provided was also awesome, which impressed me a lot while deciding to take up the one among various courses. Moreover, the trainer’s command over the technology was great. The support team was really good. Really appreciable!
Intellipaat’s Data Science certification training videos really made me excited about studying Data Science. They were so elaborate and so professionally created. I could learn Data Science from the comfort of my home, thanks to those learner-friendly videos. I am grateful to Intellipaat!
Data Science training online includes a lot of constituent components, and Intellipaat’s course provided the most comprehensive and in-depth learning experience. I really liked the real-world projects, which helped me take on a Data Science role in a reputed company much easier.
Bharat Rathore
I really appreciate the quality of the material and the content of this certification course!! Thanks to all Intellipaat team!
Excellent course, I found Intellipaat's coaching team to be talented in their respective domain. My learning was very good as it helped me in upgrading my skills, which proved to be a turning point in my career. Intellipaat's mentor was well-experienced and his teaching method was really great. This, one of the best Data Science programs helped me to get deep understanding of the technology. Moreover, the exercise and projects provided as a part of the course made me to get hands-on experience. Besides, the online support team was very helpful and offered their assistance as and when I needed via calls and emails.
Intellipaat’s Data Science classes’ videos really made me excited about studying Data Science. They were so elaborate and so professionally created. I could learn Data Science from the comfort of my home, thanks to those learner-friendly videos. I am grateful to Intellipaat!
Swetha Pandit
Intellipaat’s Data scientist courses online are well structured and taught by recognized professionals. They help one learn Data Science fast. I have found their videos to be of excellent quality. Thanks a lot!
Kavita Mehra
The classes were highly interactive and also practical oriented. The office staff was cordial. Every teaching session was recorded each day and was put online. The trainer was very patient and giving hints to solve all the questions posed to him.
Sulekha Roy
I think this online course is a good way to start learning Data Science and make a career in it. Instructors are reasonably good. Also, projects were interesting and relevant to the current industry trends.
I want to talk about the rich LMS that Intellipaat’s Data Science program offered. The extensive set of PPTs, PDFs, and other related material were of the highest quality, and due to this, my learning with Intellipaat was excellent. I could clear the Cloudera Data Scientist certification exam in the first attempt.
I was searching for Data Science courses online, and I landed on Intellipaat’s. It was really good in terms of content. The sample video provided was also awesome, which impressed me a lot while deciding to take up the course. Moreover, the trainer’s command over the technology was great. The support team was really good. Really appreciable
I had enrolled for Data science course in Intellipaat. Intellipaat is a good place for learning. Material provided by the institute is nice, course material is good but can be improved even more. I had opted for weekend classes as it was more convenient for me. The trainer was good and taught us the subject well. Support team helped me to solve technical issue whenever i faced.
Great course, I had a really good experience from this platform, they trained me well. I completed my Python training with this institute where they provided extremely good training and good support too. Further, the course instructors were really well-educated who explained all the topics with great enthu.
Genuine platform for learning. I finished my course recently from Intellipaat. The trainers were excellent in teaching. Further, the course was well-structured and the lectures are really flexible. I am currently working and I still get the time to complete the course within the given time and it is mainly possible because of the 24*7 support system and the clarity of their teaching. Besides, they make us do hands-on exercises and project, making us gain in-depth knowledge of the concepts. I strongly recommend others to take this course as well.
Great training program. It was an amazing experience learning from Intellipaat. During this covid 19, it was extremely fruitful to learn and spend ample amount of time as a part of this institute. Intellipaat has also provided great support during the course. Besides, the instructor was very supportive in the course, guidance was also given to complete assignment and project which was very helpful.
Intellipaat offers exclusive Data Science course in Houston for professionals who want to expand their knowledge base and start a career in this field. There are many reasons for choosing Intellipaat:
Intellipaat offers one of the best Data Science courses in Houston that will help you to become a successful Data Scientist. The courses like Data Analytics, Artificial Intelligence, Machine Learning, Data Science with R Certification, and others are comprehensive and tailor-made to suit you as per the industry’s needs.
If you wish to enroll in our Data Scientist training in Houston, then you need to first make a choice between online instructor-led training and self-paced training. Once you do that, you can make the payment using any major credit card, debit card, or EMI options.
Intellipaat selects subject matter experts from top MNCs, who have at least 8 to 12 years of experience in the domain, as instructors. They are qualified Data Science instructors and are selected after going through our rigorous selection process and proving their capabilities.
Intellipaat’s teaching assistants are SMEs whose main aim is to make you a certified professional in the respective domain. The trainers conduct interactive video lectures to teach the latest technologies and enrich your experience with various industry-based projects. The teaching assistance provided by Intellipaat is only available during regular hours.
Intellipaat online course comprises all the topics that are required and significant to learn so that you can master this technology. Intellipaat’s Data Scientist course comprises both basic and advanced-level concepts involved in this technology so that you can learn them and master the skills to pursue a career in this domain. Moreover, the trainers of this course are experts in the domain who spend time and effort to teach you all the concepts in detail.
Since it involves various aspects of advanced technologies, such as Machine Learning, Deep Learning, and Artificial Intelligence, among others, it is comparatively difficult to learn. However, Intellipaat’s Data Scientist training is offered by experts in this domain who have a lot of experience in the field. They make all concepts easier to understand as they explain each concept with the help of several real-life examples.
Intellipaat is one of the most affordable e-learning providers today. It offers both online training and self-paced training, and you can avail them at their respective costs. Our self-paced training costs about $264, while our online instructor-led training for the same costs $399.
Intellipaat provides various group offers and discounts for its online training as per the size and type of the particular group. If you wish to avail the discount, you need to get in touch with our course advisors who will explain to you all the details regarding it.
This online training is curated by top Data Scientists from India and the United States. These SMEs have designed the course in such a manner that even if you are from a non-technical background and have almost zero knowledge of this domain, you can still learn and adapt all concepts easily. Also, we provide practical experience through real-time projects that allow even freshers to easily grasp the concepts.
In the career mentoring session at Intellipaat, our Data Science experts offer solutions to all your queries that are based on career opportunities and the growth available in this domain.
In this online training, in collaboration with IBM, you can expect several benefits, including the following:
The IT market in Houston, Texas, is growing at a fast pace since most of the enterprises in Texas have heavily invested in this domain. If you are a certified professional, then you can make the best of this rising Data Science market.
Intellipaat does not directly forward resumes to any companies or recruiters. However, we do have a placement team that will conduct a number of mock interviews and will assist you in updating your resume to prepare you for job interviews. The team thus helps you land a lucrative job in the Data Science domain.
At Intellipaat, you can enroll in either the instructor-led online training or self-paced training. Apart from this, Intellipaat also offers corporate training for organizations to upskill their workforce. All trainers at Intellipaat have 12+ years of relevant industry experience, and they have been actively working as consultants in the same domain, which has made them subject matter experts. Go through the sample videos to check the quality of our trainers.
Intellipaat is offering the 24/7 query resolution, and you can raise a ticket with the dedicated support team at anytime. You can avail of the email support for all your queries. If your query does not get resolved through email, we can also arrange one-on-one sessions with our trainers.
You would be glad to know that you can contact Intellipaat support even after the completion of the training. We also do not put a limit on the number of tickets you can raise for query resolution and doubt clearance.
Intellipaat is offering you the most updated, relevant, and high-value real-world projects as part of the training program. This way, you can implement the learning that you have acquired in real-world industry setup. 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.
Intellipaat actively provides placement assistance to all learners who have successfully completed the training. For this, we are exclusively tied-up with over 80 top MNCs from around the world. This way, you can be placed in outstanding organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, and Cisco, among other equally great enterprises. We also help you with the job interview and résumé preparation as well.
You can definitely make the switch from self-paced training to online instructor-led training by simply paying the extra amount. You can join the very next batch, which will be duly notified to you.
Once you complete Intellipaat’s training program, working on real-world projects, quizzes, and assignments and scoring at least 60 percent marks in the qualifying exam, you will be awarded Intellipaat’s course completion certificate. This certificate is very well recognized in Intellipaat-affiliated organizations, including over 80 top MNCs from around the world and some of the Fortune 500companies.
Apparently, no. Our job assistance program is aimed at helping you land in your dream job. It offers a potential opportunity for you to explore various competitive openings in the corporate world and find a well-paid job, matching your profile. The final decision on hiring will always be based on your performance in the interview and the requirements of the recruiter.
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