Data Science Training by Experts

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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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Data Science Jobs in Kamloops

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 Kamloops, chennai and europe countries. You can find many jobs for freshers related to the job positions in Kamloops.

  • 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 Kamloops
Data Science A data scientist is a person who uses a variety of procedures, methods, systems, and algorithms to analyze data to provide actionable insights. Experts provide immersive online instructor-led seminars. Create data strategies with the help of team members and leaders. . Creative thinking, problem-solving skills, curiosity, and a drive to learn about and investigate industry trends and development, as well as teamwork, are among the soft skills required by data scientists. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. To find trends and patterns, use algorithms and modules. 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. There are numerous reasons why you should take this course. Identify and collect data from data sources.

List of All Courses & Internship by TechnoMaster

Success Stories

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 Kamloops

  • ThompsonRiversUniversity | Location details: 805 TRU Way, Kamloops, BC V2C 0C8 | Classification: Public university, Public university | Visit Online: tru.ca | Contact Number (Helpline): (250) 828-5000
 courses in Kamloops
As the us of a another time confronts the shameful legacy of residential faculties and Canada`s colonial efforts, 4-H Canada recognizes the continuing systemic and unjust remedy that Indigenous peoples hold to revel in to this day. Sustainability is a function of a method or country that may be maintained at a positive stage indefinitely. A common reference factor for the idea of sustainability is the paintings of the World Commission on Environment and Development, called the Brundtland Commission, in the 1980s. Although the scholars won capabilities to evolve to Euro-Canadian society on the KIRS, the method had terrible results on their languages, traditions, and groups. The seek committee recognizes that no unmarried person is probably to fulfill all the following criteria in same measure; nevertheless, the a success candidate could be predicted to have demonstrable revel in in:  Promoting pupil fulfillment with the aid of using assisting the improvement of revolutionary strategies that lead to splendid getting to know environments  Leading the improvement and implementation of strategic and operational plans  Promoting the usage of modern and revolutionary technology to offer gold standard get admission to to, an suitable use of, records and resources  Understanding the converting studies weather in the post-secondary sector  Participating in educational governance and policy/technique improvement and review  Committing to the development of Indigenous peoples thru better education; fostering and improving an educational surroundings welcoming of variety and intercultural engagement  Building, articulating and pursuing a imaginative and prescient thru a success shipping of targets and outcomes  Ensuring the powerful control of a balanced budget  Fostering network engagement; building, preserving and nurturing notable connections with local, regional, provincial and country wide labour markets Salary variety: $135,000 - $165,000 CDN – TRU gives a aggressive advantages package, 401-k and relocation assistance. Thompson Rivers University is strongly dedicated to fostering variety inside our network. Through a carefully designed faculty curriculum KIRS teachers aimed to modernize and assimilate Indigenous college students with the aid of using coaching guide capabilities and agriculture to male college students, and with the aid of using coaching female college students domestic financial capabilities. The University Library advances inquiry, discovery and engagement with the aid of using offering the TRU network with pleasant resources, offerings and technology to assist coaching, getting to know and studies. We understand that primarily else, proper now could be a time for mourning, and we stand with all Indigenous peoples, such as Indigenous 4-H volunteers, teenagers, and personnel, in remembering now no longer best the lives of the ones 215 kids, however the limitless different kids whose lives have been misplaced to the residential faculty system. 4-H Canada believes unequivocally that #EveryChildMatters.

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