I got your response from urbanpro regarding Data Science Using R and Python Programming. And, I completed B.Tech with MBA also Pursuing Ph.D in the field of Data Analytics and Business Intelligence in BITS Pilani,So far more than 1500 professionals trained and many colleges across India trained the students. Kindly, Share your email ID will send you the detailed course brochure. This course is designed for professionals who want to explore data analysis using R Programming and it includes Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression and Random Forest Regression and Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification and Random Forest Classification and then Clustering: K-Means and Hierarchical Clustering and then Association Rule Learning: Apriori Algorithm and Eclat and then Reinforcement Learning and then Natural Language Processing and Deep Learning: Artificial Neural Networks, Convolutional Neural Networks and Dimensionality Reduction: PCA, LDA, Kernel PCA. Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
I got your response from urbanpro regarding Data Science Using R and Python Programming. And, I completed B.Tech with MBA also Pursuing Ph.D in the field of Data Analytics and Business Intelligence in BITS Pilani,So far more than 1500 professionals trained and many colleges across India trained the students. Kindly, Share your email ID will send you the detailed course brochure. This course is designed for professionals who want to explore data analysis using R Programming and it includes Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, SVR, Decision Tree Regression and Random Forest Regression and Classification: Logistic Regression, K-NN, SVM, Kernel SVM, Naive Bayes, Decision Tree Classification and Random Forest Classification and then Clustering: K-Means and Hierarchical Clustering and then Association Rule Learning: Apriori Algorithm and Eclat and then Reinforcement Learning and then Natural Language Processing and Deep Learning: Artificial Neural Networks, Convolutional Neural Networks and Dimensionality Reduction: PCA, LDA, Kernel PCA. Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.
I come with a decade of experience in IT Industry. I own a MTech degree in Data Analytics from BITS Pilani. Along with this I have completed an extensive 6 month PGP course in Machine Learning, Big Data and Optimization from INSOFE, Hyderabad. Currently I am working as a Guest faculty for BITS PIlani. I have worked on various Machine learning projects, participated in Kaggle, AnalyticsVidhya hackathons and also won 2 scholarships in INSOFE during the PGP Course. I have worked in projects in the following areas 1) Classification 2) Regression 3) Text Mining 4) Image classification 5) Sentiment Analysis 6) Recommender Systems 7) Big Data project Tools and Technologies which I have worked on include 1) R 2) Python 3) Tableau 4) Hadoop 5) Spark 6) Spark-ML 7) Kafka 8) HIVE 9) Sqoop
I come with a decade of experience in IT Industry. I own a MTech degree in Data Analytics from BITS Pilani. Along with this I have completed an extensive 6 month PGP course in Machine Learning, Big Data and Optimization from INSOFE, Hyderabad. Currently I am working as a Guest faculty for BITS PIlani. I have worked on various Machine learning projects, participated in Kaggle, AnalyticsVidhya hackathons and also won 2 scholarships in INSOFE during the PGP Course. I have worked in projects in the following areas 1) Classification 2) Regression 3) Text Mining 4) Image classification 5) Sentiment Analysis 6) Recommender Systems 7) Big Data project Tools and Technologies which I have worked on include 1) R 2) Python 3) Tableau 4) Hadoop 5) Spark 6) Spark-ML 7) Kafka 8) HIVE 9) Sqoop
It will be full fledged course on data science where I will be guiding you throughout the course with concepts like Python, R, Numpy, Pandas, static modelling, sampling, important frameworks and library, seaborn, tensorflow, matplotlib, intro to machine learning, application of machine learning, reinforced learning, linear regression, logistic regression, decision tree, svm, knn, deep learning, rnn, ann, nltk, problem solving with 21+ projects for you.
It will be full fledged course on data science where I will be guiding you throughout the course with concepts like Python, R, Numpy, Pandas, static modelling, sampling, important frameworks and library, seaborn, tensorflow, matplotlib, intro to machine learning, application of machine learning, reinforced learning, linear regression, logistic regression, decision tree, svm, knn, deep learning, rnn, ann, nltk, problem solving with 21+ projects for you.
I have 4+ years of experience in sas programming in BFSI domain, i have a good knowledge in Clinical SAS programming also. So far i have trained 100+ students on SAS Programming and I guide you in SAS Certification also.
I have 4+ years of experience in sas programming in BFSI domain, i have a good knowledge in Clinical SAS programming also. So far i have trained 100+ students on SAS Programming and I guide you in SAS Certification also.
I am having 6 years experience in teaching data science, python and machine learning concepts. Used Pandas, Numpy libraries for Data Analytics. Used Matplotlib, Seaborn for Data Visualization. Used Scikit-Learn for Supervised, Unsupervised model in Data Science. Have good knowledge in Feature Selection, Feature Engineering, Label Encoding, Outliers Treatment, Tuning Hyperparameters concepts. Models - Linear Regression(Lasso Ridge), Logistic Regression, Decision Tree, Random Forest, Naive Bayes, SVM, KMeans Clusterng, PCA, DBScan, KNN etc. I will give questions/live examples to practise after each session. I have done many projects, so i can give real time examples. I can help in completing your assignments.
I am having 6 years experience in teaching data science, python and machine learning concepts. Used Pandas, Numpy libraries for Data Analytics. Used Matplotlib, Seaborn for Data Visualization. Used Scikit-Learn for Supervised, Unsupervised model in Data Science. Have good knowledge in Feature Selection, Feature Engineering, Label Encoding, Outliers Treatment, Tuning Hyperparameters concepts. Models - Linear Regression(Lasso Ridge), Logistic Regression, Decision Tree, Random Forest, Naive Bayes, SVM, KMeans Clusterng, PCA, DBScan, KNN etc. I will give questions/live examples to practise after each session. I have done many projects, so i can give real time examples. I can help in completing your assignments.
Machine learning, natural language processing, Image analytics and speech processing with deep learning. Python, azure, c# cloud computing, tensorflow , keras, R, time series Supervised, unsupetvise learning.
Machine learning, natural language processing, Image analytics and speech processing with deep learning. Python, azure, c# cloud computing, tensorflow , keras, R, time series Supervised, unsupetvise learning.
Over 4 years of experience in all facets of web development, from personally meeting with clients to discuss their goals in having a web presence, to research and analysis, design, development, testing, and implementation of code and applications, as well as a variety of graphic design and artwork. Has been both a team leader and a team member, and knows what it takes to get things done. Doesn’t only create working inter/intranet sites, but creates better ones and continually strives to improve a site's usability, functionality, and navigation throughout its life cycle.
Over 4 years of experience in all facets of web development, from personally meeting with clients to discuss their goals in having a web presence, to research and analysis, design, development, testing, and implementation of code and applications, as well as a variety of graphic design and artwork. Has been both a team leader and a team member, and knows what it takes to get things done. Doesn’t only create working inter/intranet sites, but creates better ones and continually strives to improve a site's usability, functionality, and navigation throughout its life cycle.
I have been topper of my school in board exams. I have done Engineering and MBA. I have worked for various MNC companies.So i believe i can help kids with my broad ideas in their studies helping them to attain a better perspective towards studies and life.
I have been topper of my school in board exams. I have done Engineering and MBA. I have worked for various MNC companies.So i believe i can help kids with my broad ideas in their studies helping them to attain a better perspective towards studies and life.
The AppliedAICourse attempts to teach students/course-participants some of the core ideas in machine learning, data-science and AI that would help the participants go from a real world business problem to a first cut, working and deployable AI solution to the problem. Our primary focus is to help participants build real world AI solutions using the skills they learn in this course. No prerequisites. Given our background in the industry, we believe that students completing this course and building a strong portfolio consisting of multiple projects stand a good chance of getting an AI engineer job in the industry. But, we cannot guarantee that. We would surely refer you to various teams, hiring managers and recruiters in the industry who are looking to hire AI engineers. This course will focus on practical knowledge more than mathematical or theoretical rigor. That doesn't mean that we would water down the content. We will try and balance the theory and practice while giving more preference to the practical and applied aspects of AI as the course name suggests. Through the course, we will work on 20+ case studies of real world AI problems and datasets to help students grasp the practical details of building AI solutions. For each idea/algorithm in AI, we would provide examples to provide the intuition and show how the idea to used in the real world.
The AppliedAICourse attempts to teach students/course-participants some of the core ideas in machine learning, data-science and AI that would help the participants go from a real world business problem to a first cut, working and deployable AI solution to the problem. Our primary focus is to help participants build real world AI solutions using the skills they learn in this course. No prerequisites. Given our background in the industry, we believe that students completing this course and building a strong portfolio consisting of multiple projects stand a good chance of getting an AI engineer job in the industry. But, we cannot guarantee that. We would surely refer you to various teams, hiring managers and recruiters in the industry who are looking to hire AI engineers. This course will focus on practical knowledge more than mathematical or theoretical rigor. That doesn't mean that we would water down the content. We will try and balance the theory and practice while giving more preference to the practical and applied aspects of AI as the course name suggests. Through the course, we will work on 20+ case studies of real world AI problems and datasets to help students grasp the practical details of building AI solutions. For each idea/algorithm in AI, we would provide examples to provide the intuition and show how the idea to used in the real world.
I am having hands-on experience on Salesforce Cloud Platform and dealing with Niche Technologies. Trained multiple professionals. Real time experience in providing the advanced training.Industry Solutions and Best practices.
I am having hands-on experience on Salesforce Cloud Platform and dealing with Niche Technologies. Trained multiple professionals. Real time experience in providing the advanced training.Industry Solutions and Best practices.
Around 3+ years of working as data scientist with over all 16 years of IT experience in development, support and implementation with various client server and enterprise applications. Able to effectively communicate complex technical information in easy to understand language to aid comprehension. A young, motivated professional with a unique blend of business experience, technical skills and statistical knowledge, bringing to the table the ability to combine business development with technical applications. Passionate about interaction and share knowledge with colleagues in order to develop world-class solutions to real world challenge.
Around 3+ years of working as data scientist with over all 16 years of IT experience in development, support and implementation with various client server and enterprise applications. Able to effectively communicate complex technical information in easy to understand language to aid comprehension. A young, motivated professional with a unique blend of business experience, technical skills and statistical knowledge, bringing to the table the ability to combine business development with technical applications. Passionate about interaction and share knowledge with colleagues in order to develop world-class solutions to real world challenge.
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