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 Calgary

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

  • 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 Calgary
Data Science . You may learn all of the skills and talents required to become a data scientist by enrolling in the top data science online courses in Calgary. This curriculum prepares you to work in a variety of Data Science professions and earn top-dollar wages. 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. 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. 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. You'll have a personal mentor who will keep track of your development. Experts provide immersive online instructor-led seminars. Cleaning and validating data to ensure that it is accurate and consistent. Create data strategies with the help of team members and leaders.

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 Calgary

  • CalgaryBoardOfEducation | Location details: 1221 8 St SW, Calgary, AB T2R 0L4 | Classification: Educational institution, Educational institution | Visit Online: cbe.ab.ca | Contact Number (Helpline): (403) 817-4000
  • ChinookLearningServices-AdultESL | Location details: 1304 44 St SE, Calgary, AB T2A 1M8 | Classification: English language school, English language school | Visit Online: chinooklearningservices.com | Contact Number (Helpline): (403) 777-6330
  • MountRoyalUniversitySpringbankCampus | Location details: 143 Maclaurin Dr, Calgary, AB T3Z 3S4 | Classification: School, School | Visit Online: mtroyal.ca | Contact Number (Helpline): (403) 288-9551
  • BowValleyCollege,SouthCampus | Location details: 345 6 Ave SE, Calgary, AB T2G 4V1 | Classification: College, College | Visit Online: bowvalleycollege.ca | Contact Number (Helpline): (403) 410-1400
  • SchulichSchoolOfEngineering | Location details: 622 Collegiate Pl NW, Calgary, AB T2N 4V8 | Classification: University department, University department | Visit Online: schulich.ucalgary.ca | Contact Number (Helpline): (403) 220-5738
  • Innovel(InnovelInternationalInc.) | Location details: 111 Westridge Crescent SW, Calgary, AB T3H 5C9 | Classification: Business management consultant, Business management consultant | Visit Online: innovel.net | Contact Number (Helpline): +1 833-462-4453
  • MountRoyalUniversity | Location details: 4825 Mt Royal Gate SW, Calgary, AB T3E 6K6 | Classification: University, University | Visit Online: mtroyal.ca | Contact Number (Helpline): (403) 440-6111
  • CBe-learn|CalgaryBoardOfEducation | Location details: 2336 53 Ave SW, Calgary, AB T3E 1L2 | Classification: School, School | Visit Online: cbelearn.ca | Contact Number (Helpline): (403) 777-7971
  • ABMCollege-CalgaryCampus | Location details: 112 28 St SE #200, Calgary, AB T2A 6J9 | Classification: College, College | Visit Online: abmcollege.com | Contact Number (Helpline): (403) 719-4300
  • UniversityOfCalgaryContinuingEducation | Location details: 906 8 Ave SW #226, Calgary, AB T2P 1H9 | Classification: Educational institution, Educational institution | Visit Online: conted.ucalgary.ca | Contact Number (Helpline): (403) 220-2866
  • InstituteOfSoftwareTraining | Location details: Savanna Blvd NE, Calgary, AB T3J 0X3, Canada | Classification: Software training institute, Software training institute | Visit Online: | Contact Number (Helpline): +1 587-581-5528
  • TechCareers | Location details: 734 7 Ave SW Suite 240, Calgary, AB T2P 3P8 | Classification: Training centre, Training centre | Visit Online: techcareers.ca | Contact Number (Helpline): +1 855-585-8324
  • BowValleyCollege,SouthCampus | Location details: 345 6 Ave SE, Calgary, AB T2G 4V1, Canada | Classification: College, College | Visit Online: bowvalleycollege.ca | Contact Number (Helpline): +1 403-410-1400
  • UniversityOfCalgary | Location details: 2500 University Dr NW, Calgary, AB T2N 1N4 | Classification: University, University | Visit Online: ucalgary.ca | Contact Number (Helpline): (403) 220-5110
  • InstituteOfITTrainingCanada | Location details: 2770 3 Ave NE #221, Calgary, AB T2A 2L5 | Classification: Institute of technology, Institute of technology | Visit Online: iofit.ca | Contact Number (Helpline): (403) 207-0273
  • SAS | Location details: 517 10 Ave SW #850, Calgary, AB T2R 0A8 | Classification: Software company, Software company | Visit Online: support.sas.com | Contact Number (Helpline): (403) 265-5177
 courses in Calgary
33-biggest metropolis and fifth-biggest metropolitan place in Canada. [36] In spring 1875, 3 priests – Lacombe, Remus, and Scollen – constructed a small log cabin at the banks of the Elbow River. Calgary became named after Calgary at the Isle of Mull, Scotland, United Kingdom. In Biblical instances there have been humans right here. [19][21] In Kutenai language, the metropolis is called ʔaknuqtapȼik`. In the Tsuutʼina language (Sarcee), the place is called Guts`ists`i (older orthography, Kootsisáw) meaning "elbow". In the autumn of 1875, the web website online have become a submit of the North-West Mounted Police (NWMP) (now the Royal Canadian Mounted Police or RCMP). 33 maximum livable metropolis withinside the world, rating first in Canada and in North America. [24][25][29][30][31] In 2017, the Stoney Nakoda despatched an software to the Government of Alberta, to rename Calgary as Wichispa Oyade meaning "elbow town";[32] however, this became challenged via way of means of the Piikani Blackfoot. [18] Alternatively, the call is probably Gaelic Cala ghearraidh, meaning "seashore of the meadow (pasture)", or Gaelic for either "clean walking water" or "bay farm".

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