Data Science Training by Experts

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Our Training Process

Data Science - Syllabus, Fees & Duration

MODULE 1

  • The Data Science Process
  • Apply the CRISP-DM process to business applications
  • Wrangle, explore, and analyze a dataset
  • Apply machine learning for prediction
  • Apply statistics for descriptive and inferential understanding
  • Draw conclusions that motivate others to act on your results

MODULE 2

  • Communicating with Stakeholders
  • Implement best practices in sharing your code and written summaries
  • Learn what makes a great data science blog
  • Learn how to create your ideas with the data science community

MODULE 3

  • Software Engineering Practices
  • Write clean, modular, and well-documented code
  • Refactor code for efficiency
  • Create unit tests to test programs
  • Write useful programs in multiple scripts
  • Track actions and results of processes with logging
  • Conduct and receive code reviews

MODULE 4

  • Object Oriented Programming
  • Understand when to use object oriented programming
  • Build and use classes
  • Understand magic methods
  • Write programs that include multiple classes, and follow good code structure
  • Learn how large, modular Python packages, such as pandas and scikit-learn, use object oriented programming
  • Portfolio Exercise: Build your own Python package

MODULE 5

  • Web Development
  • Learn about the components of a web app
  • Build a web application that uses Flask, Plotly, and the Bootstrap framework
  • Portfolio Exercise: Build a data dashboard using a dataset of your choice and deploy it to a web application

MODULE 6

  • ETL Pipelines
  • Understand what ETL pipelines are
  • Access and combine data from CSV, JSON, logs, APIs, and databases
  • Standardize encodings and columns
  • Normalize data and create dummy variables
  • Handle outliers, missing values, and duplicated data
  • Engineer new features by running calculations • Build a SQLite database to store cleaned data

MODULE 7

  • Natural Language Processing
  • Prepare text data for analysis with tokenization, lemmatization, and removing stop words
  • Use scikit-learn to transform and vectorize text data
  • Build features with bag of words and tf-idf
  • Extract features with tools such as named entity recognition and part of speech tagging
  • Build an NLP model to perform sentiment analysis

MODULE 8

  • Machine Learning Pipelines
  • Understand the advantages of using machine learning pipelines to streamline the data preparation and modeling process
  • Chain data transformations and an estimator with scikit- learn’s Pipeline
  • Use feature unions to perform steps in parallel and create more complex workflows
  • Grid search over pipeline to optimize parameters for entire workflow
  • Complete a case study to build a full machine learning pipeline that prepares data and creates a model for a dataset

MODULE 9

  • Experiment Design
  • Understand how to set up an experiment, and the ideas associated with experiments vs. observational studies
  • Defining control and test conditions
  • Choosing control and testing groups

MODULE 10

  • Statistical Concerns of Experimentation
  • Applications of statistics in the real world
  • Establishing key metrics
  • SMART experiments: Specific, Measurable, Actionable, Realistic, Timely

MODULE 11

  • A/B Testing
  • How it works and its limitations
  • Sources of Bias: Novelty and Recency Effects
  • Multiple Comparison Techniques (FDR, Bonferroni, Tukey)
  • Portfolio Exercise: Using a technical screener from Starbucks to analyze the results of an experiment and write up your findings

MODULE 12

  • Introduction to Recommendation Engines
  • Distinguish between common techniques for creating recommendation engines including knowledge based, content based, and collaborative filtering based methods.
  • Implement each of these techniques in python.
  • List business goals associated with recommendation engines, and be able to recognize which of these goals are most easily met with existing recommendation techniques.

MODULE 13

  • Matrix Factorization for Recommendations
  • Understand the pitfalls of traditional methods and pitfalls of measuring the influence of recommendation engines under traditional regression and classification techniques.
  • Create recommendation engines using matrix factorization and FunkSVD
  • Interpret the results of matrix factorization to better understand latent features of customer data
  • Determine common pitfalls of recommendation engines like the cold start problem and difficulties associated with usual tactics for assessing the effectiveness of recommendation engines using usual techniques, and potential solutions.

Download Syllabus - Data Science
Course Fees
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20+
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25+

Data Science Jobs in Nizwa

Enjoy the demand

Find jobs related to Data Science in search engines (Google, Bing, Yahoo) and recruitment websites (monsterindia, placementindia, naukri, jobsNEAR.in, indeed.co.in, shine.com etc.) based in Nizwa, chennai and europe countries. You can find many jobs for freshers related to the job positions in Nizwa.

  • Data Scientist
  • Data Analyst
  • Data Engineer
  • Data Storyteller
  • Machine Learning Scientist
  • Machine Learning Engineer
  • Business Intelligence Developer
  • Database Administrator
  • ML Engineer
  • Computer Vision Engineer

Data Science Internship/Course Details

Data Science internship jobs in Nizwa
Data Science Exercises, tasks, and projects that are completed in real-time 24 hours a day, 7 days a week, A large network of like-minded newbies, an industry-recognized intellipaat credential, and individualized employment support Several data scientist responsibilities are listed below. The top Data Science course online for professionals who wish to expand their knowledge base and start a career in this industry is NESTSOFT in Nizwa. Data Science provides a diverse set of tools for analyzing data from a range of sources, including financial records, multimedia files, marketing forms, sensors, and text files. Cleaning and validating data to ensure that it is accurate and consistent. A Data Scientist is a highly skilled someone with advanced mathematical, statistical, scientific, analytical, and technical abilities who can prepare, clean, and validate organized and unstructured data for industries to utilize in making better decisions. Today's Data Scientists must possess a wide range of abilities, including the ability to work with large amounts of data, parse that data, and translate it into an easily comprehensible format from which business insights may be drawn. You'll have a personal mentor who will keep track of your development. Experts provide immersive online instructor-led seminars. . The Data Science Process, Communicating with Stakeholders, Software Engineering Practices, Object-Oriented Programming, Web Development, ETL Pipelines, Natural Language Processing, Machine Learning Pipelines, Experiment Design, Statistical Concerns of Experimentation, A/B Testing, and Introduction to Recommendation Engines are some of the topics covered in.

List of All Courses & Internship by TechnoMaster

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The enviable salary packages and track record of our previous students are the proof of our excellence. Please go through our students' reviews about our training methods and faculty and compare it to the recorded video classes that most of the other institutes offer. See for yourself how TechnoMaster is truly unique.

List of Training Institutes / Companies in Nizwa

  • LuLuHypermarket-Nizwa | Location details: Nizwa, Oman | Classification: Hypermarket, Hypermarket | Visit Online: luluhypermarket.com | Contact Number (Helpline): +968 25 415900
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  • LuLuHypermarket-Nizwa | Location details: Nizwa, Oman | Classification: Hypermarket, Hypermarket | Visit Online: luluhypermarket.com | Contact Number (Helpline): +968 25 415900
  • LuLuHypermarket-Nizwa | Location details: Nizwa, Oman | Classification: Hypermarket, Hypermarket | Visit Online: luluhypermarket.com | Contact Number (Helpline): +968 25 415900
  • Schlumberger,Nizwa | Location details: RFQQ+V4M، طيمسا، Oman | Classification: Oil field equipment supplier, Oil field equipment supplier | Visit Online: slb.com | Contact Number (Helpline):
  • Omantel | Location details: VGRH+9W4, Nizwa, Oman | Classification: Telecommunications, Telecommunications | Visit Online: omantel.om | Contact Number (Helpline): +968 25 410444
  • Centrepoint | Location details: Nizwa Grand Mall, Nizwa 611, Oman | Classification: Clothing store, Clothing store | Visit Online: centrepointstores.com | Contact Number (Helpline): +968 25 431840
 courses in Nizwa
In addition, globalization of the world economic system has introduced its very own strains, demanding situations and possibilities. In reaction to those demands, the eye of the Ministry of Education in recent years has shifted farfar from worries approximately access (considering that ninety seven percentage of fundamental college-age Omanis are enrolled in schooling) closer to tries to qualitatively enhance and growth the relevance of the schooling device with the intention to put together our college students to fulfill the demanding situations of a knowledge-primarily based totally economic system. These developments, coupled with the Government`s coverage to “Omanize” the workforce, have supposed that the united states of america`s desires in phrases of schooling have dramatically changed. To all intents and purposes, therefore, the united states of america became beginning with what became really a smooth slate in phrases of complete instructional provision. There have been over 43,000 teachers, of which 89 percentage have been Omani. The clean priorities of the united states of america have been to construct the desired instructional infrastructure; to behavior a teacher recruitment software, specifically from abroad; and to broaden a curriculum. Within a length of forty years, the scenario has been absolutely transformed. I am assured that the record show to be of massive advantage to the Sultanate in assisting it to enhance its instructional device in phrases of access, equity, high-satisfactory and efficiency. The Ministry of Education is currently engaged in some of predominant reform tasks across the complete device. With the sturdy political will and dedication of His Majesty Sultan Qaboos and his Government to the united states of america`s instructional improvement, we consider we can efficiently put together our residents for the first-rate demanding situations going through our country via our venture to offer all of them with an Education of Quality.

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