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 am a senior Solution Architect working in the AI/ ML domain with expertise and experience in architecting, building solutions for various AI/ML use cases.
I am a senior Solution Architect working in the AI/ ML domain with expertise and experience in architecting, building solutions for various AI/ML use cases.
Data Scientist with 4+ years of hands-on experience in creating end-to-end analytics solutions for clients' complex business problems. Focused on building AI/ML and MLops architecture for central cloud AWS, GCP, and Azure. Assisted and Led various successful sales pursuits for Health care, Life Sciences, Banking, and Retail clients
Data Scientist with 4+ years of hands-on experience in creating end-to-end analytics solutions for clients' complex business problems. Focused on building AI/ML and MLops architecture for central cloud AWS, GCP, and Azure. Assisted and Led various successful sales pursuits for Health care, Life Sciences, Banking, and Retail clients
I am a junior software engineer and my bachelor's specialises in Artificial intelligence and Machine Learning. My key skills are Python, Data Science, and Web Development. I have practical experience working with real-world projects and open-source contribution
I am a junior software engineer and my bachelor's specialises in Artificial intelligence and Machine Learning. My key skills are Python, Data Science, and Web Development. I have practical experience working with real-world projects and open-source contribution
I can teach every topic very easily and make it stronger for the students.
I can teach every topic very easily and make it stronger for the students.
With our intuitive platform, learning has never been easier. Dive into interactive lessons, complete hands-on projects, test your knowledge with quizzes, and track your progress every step of the way, all from the comfort of your own home and at your own pace.
With our intuitive platform, learning has never been easier. Dive into interactive lessons, complete hands-on projects, test your knowledge with quizzes, and track your progress every step of the way, all from the comfort of your own home and at your own pace.
I have 3+ years of experience as a data scientist. Good hands on in python and R programming. Have good experience in dealing with unstructured data, data handling and data exploration. Good experience in machine learning models and deep learning models.
I have 3+ years of experience as a data scientist. Good hands on in python and R programming. Have good experience in dealing with unstructured data, data handling and data exploration. Good experience in machine learning models and deep learning models.
I have completed my data science course in 5g analytics gachibowli. I am very good at statistics.And I can do machine learning algorithms in both R as well as python.I have done some projects also. You can find that in my resume
I have completed my data science course in 5g analytics gachibowli. I am very good at statistics.And I can do machine learning algorithms in both R as well as python.I have done some projects also. You can find that in my resume
I am working as statistical programmer in multinational organisation. I have total of 3 years of experience in SAS programming. I have worked on SDTM, ADaM, TLF, CRF Annotations, define.xml and till submission of the data to regulatory authorities.
I am working as statistical programmer in multinational organisation. I have total of 3 years of experience in SAS programming. I have worked on SDTM, ADaM, TLF, CRF Annotations, define.xml and till submission of the data to regulatory authorities.
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