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Data Science Training

Mmakes you an expert in building the applications by leveraging capabilities of Data transformation using Map Reduce (RMR), Random Forest Classifier, Integrating R with Hadoop using R, Sub-setting data & more.

Data Science Training Details
Track Regular Track Weekend Track Fast Track
Course Duration 30 Hrs 8 Weekends 15 Days
Hours 1hr/day 2 Hours a day 2 Hours a day

 

 

Modes of Training


Self Paced Video Learning

Access to High Quality pre-recorded Data Science  Training videos (from a previous live training).

  Instructor Led Live Training

Live Online training by Certified & industry expert Trainers & On Demand Dedicated Cloud lab and LMS access.

Corporate Training

Self-Paced e-learning and/or instructor-led Live online training options & Learning Management System access.

 

 

Course Curriculum

Key Features
What are the Objectives & Learning Outcomes of Data Science Training? 00:00:00
Objectives and learning outcomes, Who should do this course & What projects are included in this course?
Who should do Data Science Training course? 00:00:00
Data Science is being used by most of the world’s top multinationals. Data Science professionals are earning very high salaries when compared with other technologies.With high demand and a number of job opportunities in this field,  the following people will get benefited from this course Information Architects Data analysts Business analysts Freshers/Graduates keep to take up the role of a data scientist BI professionals
What projects are included in Data Science Training course? 00:00:00
An in-depth knowledge on data science project which focuses on all the critical components of data science will be provided by our trainer. As a result, you can increase your visibility and increase your efficiency and draw real connections between different components of data science. You will also get the complete material covering all the aspects of this project.
Curriculum
Data Science Bascis 00:00:00
Introduction to Data Science What makes a Data Scientist? AI & Machine Learning – An Introduction. Hands on Python Basic Statistics with Python+Tensorflow& R Measures of Central tendency Measures of Dispersion Skewness and Kurtosis Linear Algebra Review Hypothesis, Parametric and Non-Parametric Tests Sample and Population Formulate the Hypothesis Select an Appropriate Test Choose level of Significance Calculate Test Statistics
Probability Theory 00:00:00
Hands onwith Python+Tensorflow. Events and their Probabilities Rules of Probability Conditional Probability and Independence Distribution of a Random Variable
Hands on Python 00:00:00
k-Nearest Neighbors and Generalization. K Nearest Neighbours Algorithm for Classification with case study Lazy Learning Notion  Computation of Distance Matrix  The Optimum K values . Data Transformations as a Pre-Processing Phase Model Building on Training Data Set  Model Validation on Testing Data Set Evaluation of Model Advantages & Disadvantages of KNN Models
Hands on with Python+Tensorflow 00:00:00
Model & Cost function, Linear Regression with One Variable Solving Linear, Logistic regression using Maximum Likelihood Estimation and Linear Regression Linear Regression with Multiple Variables Logistic Regression with Multivariate Logistic Regression Applications of Logistic Regression, the link to Linear Regression and Machine Learning Determine the Probability Compare the Probability and Make Decision One Sample T-Test Two Independent Samples Tests  Paired T-test,Proportional Test  Non-Parametric One Sample Test  Chi Square,Test Z Test,F Test Optimization in Python Kernels Introduction Visualization and dimensionality reduction Principal Component Analysis (PCA) Kernel PCA Locally-Linear Embedding (LLE) t-distributed Stochastic Neighbor Embedding (t-SNE) Association rule learning,Apriori,Eclat
Decision Trees with Case study 00:00:00
Understanding Decision tree  Decision Tree terminology  Hands on Python Building decision Tree  Decision tree evaluation
Support Vector Machine Fundamentals 00:00:00
Hands on with Python+Tensorflow. Linear Classifiers: Support Vector Machines Multi-Class Classification Kernelized Support Vector Machines Cross-Validation
Data Science training Project 00:00:00
The aim of the project module is to let you have an idea of what a project is, problem statement, various approaches and solving algorithms. Project Discussion Problem Statement and Analysis Various approaches to solve a Data Science Problem Pros and Cons of different approaches and algorithms
Practice Test & Interview Questions for Data Science Training 00:00:00
Tableau offers advanced Data Science  interview questions and answers along with Data Science resume samples. Take a free sample practice test before appearing in the certification to improve your chances of scoring high.
FAQ's
Who Are The Trainers? 00:00:00
Our trainers have relevant experience in implementing real-time solutions on different queries related to different topics. Tableau verifies their technical background and expertise.
What If I Miss A Class? 00:00:00
We record each LIVE class session you undergo through and we will share the recordings of each session/class.
Who Are Our Customers? 00:00:00
As we are one of the leading providers of Live Instructor LED training, We have customers from USA, UK, Canada, Australia, UAE, Qatar, NZ, Singapore, Malaysia, India and other parts of the world. We are located in USA. Offering Online Training in Cities like New York, New jersey, Dallas, Seattle, Baltimore, Houston, Minneapolis, Los Angeles, San Francisco, San Jose, San Diego, Washington DC, Chicago, Philadelphia, St. Louis, Edison, Jacksonville, Towson, Salt Lake City, Davidson, Murfreesboro, Atlanta, Alexandria, Sunnyvale, Santa clara, Carlsbad, San Marcos, Franklin, Tacoma, California, Bellevue, Austin, Charlotte, Garland, Raleigh-Cary, Boston, Orlando, Fort Lauderdale, Miami, Gilbert, Tempe, Chandler, Scottsdale, Peoria, Honolulu, Columbus, Raleigh, Nashville, Plano, Toronto, Montreal, Calgary, Edmonton, Saint John, Vancouver, Richmond, Mississauga, Saskatoon, Kingston, Kelowna, Hyderabad, Bangalore, Pune, Mumbai, Delhi, Dubbai, Doha, Melbourne, Brisbane, Perth, Wellington, Auckland etc…
How to Get Certified in Data Science Training? 00:00:00
The detailed information regarding certifications is available on clicking this link.
Is There Any Offer / Discount I Can Avail? 00:00:00
There are some Group discounts available if the participants are more than 2.
Are These Classes Conducted Via Live Online Streaming? 00:00:00
Yes. All the training sessions are LIVE Online Streaming using either through WebEx or GoToMeeting, thus promoting one-on-one trainer student Interaction.
Will I Be Working On A Project? 00:00:00
The Training itself is Real-time Project Oriented.
If I Cancel My Enrollment, Will I Get The Refund? 00:00:00
If you are enrolled in classes and/or have paid fees, but want to cancel the registration for certain reason, it can be attained within 48 hours of initial registration. Please make a note that refunds will be processed within 30 days of prior request.
Certifications
How to Get Certified in Data Science Training? 00:00:00
The detailed information regarding certifications is available on clicking this link.

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