RavhIT Data Science Online Ccourse

Data Science Training



Course Amount: $999

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Data Science Training Los Angeles, CA

 

It is easy to accelerate your career in the ever-growing field of Data Science with our exclusive, affordable Data Science online course training.

Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills.

In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.

In this Data Science course training, you will learn Data Analytics, statistical modelling, Machine Learning algorithms, recommendation engines, text mining, and more. You will also gain knowledge about statistical R calculations, developing e-commerce recommendation engines, and using market basket analytics in retail.

 We are providing Data Science training with highly experienced real-time industry experts. Our team of Data Science trainers offers a deep in-depth trailing with real-time project scenarios with updated technologies by using simple programming tools.

KEY Highlights

   
Get noticed by top companies through our professional job assistance.
 
35 hours of in-depth training programs with realtime scenarions.
 
Get trained by the highly experienced certified industry experts.
Upgraded sylabus with Industry oriented concepts for in-depth knowledge.
 
15+ In- demand tools & skills will help in  Technical Assistance.
 
Every session will be live and provides you hands-on experience training.

Training Advantages

35 contact hours

Industry case studies

Hands-on Projects

Real time training

Course Outcomes

 

Core Concepts

Core computer science concepts from leading industry experts. 

Application Testing

Build an end-to-end application and test it with exciting features.

Certification

Earn an industry-recognized course completion certificate.

Data Science Certification Course Contents

Python Core (Complete Hands-on)

  • What is Python?
  • Why Python?
  • Installation of python
  • Conditions
  • Loops
  • Break statement
  • Continue statement
  • Range functions
  • Command-line arguments

Strings & Collections

  • String Object Basics
  • String Methods
  • Splitting and Joining Strings
  • String format functions
  • List Object Basics
  • List Methods
  • Tuples
  • Sets
  • Frozen sets
  • Iterators
  • Generators
  • Decorators
  • Python Advanced concepts

  • Creating Classes and Objects
  • Inheritance
  • Multiple Inheritance
  • Working with files
  • Reading and Writing Files
  • Using Standard Modules
  • Creating custom modules
  • Exceptions Handling with Try-except
  • Finally, in exception handling
  • NUMPY

  • ND array Object
  • Data Types
  • Array Attributes
  • Array Creation Routines
  • Array from Existing Data
  • Array from Numerical Ranges
  • Indexing & Slicing
  • Advanced Indexing
  • Broadcasting
  • Iterating Over Array
  • Array Manipulation
  • Binary Operators
  • String Functions
  • Mathematical Functions
  • Arithmetic Operations
  • Statistical Functions
  • Sort, Search & Counting Functions
  • Byte Swapping
  • Copies & Views
  • Matrix Library
  • Pandas

  • Series
  • Data Frame
  • Panel
  • Basic Functionality
  • Re indexing
  • Iteration
  • Sorting
  • Working with Text Data
  • Options & Customization
  • Indexing & Selecting Data
  • Window Functions
  • Date Functionality
  • Time delta
  • Categorical Data
  • Visualization
  • IO Tools
  • Matplotlib

  • Introduction & Installation
  • Format strings in the plot function
  • Axes labels
  • Legend
  • Grid
  • Bar chart
  • Histograms
  • Pie chart
  • Save fig
  • Scatter plots
  • Sub plots
  • Seaborn

  • Introduction & Installation
  • Bar plot
  • Distributed plot
  • Box plot
  • Strip plot
  • Pair grid
  • Violin Plot
  • Cluster Map
  • Heat Map
  • Facet Grid
  • KDE plot
  • Joint plot
  • Reg plot
  • Pair plot
  • Features Engineering

  • Numerical variables
  • Categorical variables
  • Missing Values
  • Outliers
  • Mean and median imputation
  • Random sample imputation
  • Dummy variables
  • One hot encoding
  • Train and test data split
  • Save model using pickle
  • Machine Learning-Introduction

  • What is Machine Learning
  • Machine Learning Types supervised learning o Unsupervised learning o Reinforcement learning o Deep learning
  • Linear regression
  • Multiple linear regression
  • Gradient Descent
  • Ridge regression
  • Lasso regression
  • Logistic regression-Binary classification
  • Logistic regression-Multi Class classification
  • K Nearest Neighbors (KNN)
  • Naive Bayes
  • Decision trees
  • Random forests
  • Un Supervised Learning
  • K Means Clustering
  • Optimization techniques

  • K fold cross-validation
  • Hyperparameter tuning o Grid Search CV o Randomized CV
  • Ensemble Methods o Boosting o Bagging
  • Deep learning

  • Introduction to Tensor flow
  • Constant
  • Place holders
  • Variables
  • MLNN
  • Neurons
  • Weights
  • Activations
  • Networks of Neurons
  • Training Networks
  • Backpropagation
  • Gradient Descent
  • CNN
  • Classification learning
  • Flatten
  • Fully Connected  SoftMax
  • Interview Preparation

  • 3 Real-Time Projects
  • Deployment on multiple platforms
  • Discussion on project explanation in the interview
  • Data scientist roles and responsibilities
  • Data scientist day to day work
  • One to One resume Discussion with project, technology and Experience.
  • Data Science Training FAQ’S

     

    What is the smallest unit of information commonly in use in today’s computers?

    A Bit

    What is the cost of each software license for the R open-source data analysis program?

    R is free

    What is the name of the data object that R uses to store a rectangular dataset of cases and variables?

    A Data Frame

    What do the following R functions stand for?

    1. c () stands for  concatenates data elements together
    2. <- stands for assignment arrow
    3. data frame () makes a data frame from separate vectors
    4. str () reports the structure of a data object

    summary () reports data modes/types and data overview

    What are the most important skills for an aspiring data scientist to acquire?

    Machine learning, data mining, information retrieval, statistics, data and information visualization, databases (modelling, organizing and querying), data structures including indexing schemes, programming including Python, R, SAS, Hadoop and Spark, graph/network analysis, natural language processing, optimization, and modelling & simulation.

    What do the following R functions stand for?

    Positively (right) skewed

    What are the most common Big Data problems?

    1. Modelling true risk
    2. Customer churn analysis
    3. Recommendation engine
    4. Ad targeting
    5. POS transaction analysis
    6. Analyzing network data to predict failure
    7. Threat analysis
    8. Trade surveillance
    9. Search Quality
    10. Data sandbox

    Which are the two main components of core Hadoop?

    1.Hadoop Distributed File System (HDFS) 2.MapReduce

    Name the tools typically used in Big Data scenarios?

    1.NoSQL CouchDB, Cassandra, BigTable, Hbase

     2.MapReduce Hadoop Hive Pig Cascading

    3.Storage S3 Hadoop Distributed File System

    4.Servers EC2, Beanstalk, Elastic, Herokee

    5.Processing R, Mechanical Turk, Datameer, BigSheets, ElasticSearch



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    Customer Testimonials

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    This is an excellent practical course, giving the opportunity to get acquainted with both theoretical and practical work in Business Analysis.

    Henry James

    Chicago

    The best training professionals I found for automation testing training, faculties are highly experienced, explained every concept in-depth with real-time project scenarios.

    Jennifer

    San Diego

    Happy to start off my selenium career here, this is by the far the best institute I have ever got for Selenium. Very eloquent tutorial. Outstanding Training with great examples.

    Sophia

    Dallas

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