This Data Science training course in San Francisco helps you master data analytics, business analytics, data modeling, Machine Learning algorithms, k-means clustering, Naïve Bayes, etc. This Data Scientist training will help you learn R statistical computing, building a recommendation engine for e-commerce, recommending movies, and deploying market basket analysis in the retail sector. Get the best online Data Science training in San Francisco from top Data Scientists.
Intellipaat offers the most in-depth and comprehensive Data Scientist training in San Francisco. This entire Data Science course in San Francisco is developed keeping in mind the industry requirements and includes the aspects of data mining, data analysis, discovery and transformation, working with Machine Learning algorithms, Deep Learning, and gathering valuable business insights.
Intellipaat is a premier online training institute that helps you master concepts such as:
Intellipaat’s online Data Scientist course in San Francisco is exclusively designed by industry experts for:
The Silicon Valley has no shortage of tech companies that are ready to offer top salaries when it comes to hiring top-notch Data Scientists and Data Analysts. Due to this, when compared to other cities, this city offers the best salary in the United States.
Anybody can take up this course regardless of prior skills. Although, knowledge of statistics and mathematics is beneficial.
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.
|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|
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 skills.
This 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.
According to Glassdoor, the average income of a Data Scientist in San Francisco is US$122,801 per year.
Top companies that hire Data Scientists are:
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
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
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
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
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
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
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
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
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
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
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
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
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 by the top 80+ MNCs, such as Ericsson, Cisco, Cognizant, Sony, Mu Sigma, Standard Chartered, TCS, Genpact, etc.
Intellipaat offers an exclusive Data Science course in San Francisco with placement 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 leading Data Science courses in San Francisco that will help you to learn about practical implementations on real-time live projects. The courses like Artificial Intelligence, Machine Learning, Data Analytics, R Certification, Python for Data Science, Python, Business Analytics and others are comprehensive and tailor-made to suit you as per the industry’s needs.
Intellipaat online course comprises all the topics that are required and significant to learn so that you can master this technology. Intellipaat’s 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.
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.
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 US$264, while our online instructor-led training for the same costs US$399.
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 domain.
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.
If you wish to enroll in our Data Scientist training in San Francisco, 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.
Since it is the technology hub of not just the United States but the entire world, the domain is really heating up in the city, thanks to the biggest IT companies and the next billion-dollar startup companies that are in a mad scramble to recruit the best talent in the domain at top salaries.
In this online training, in collaboration with IBM, you can expect several benefits, including the following:
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 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 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.
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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