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
10000+
20+
50+
25+

Data Science Jobs in Melbourne

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

  • 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 Melbourne
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 Melbourne. Experts provide immersive online instructor-led seminars. Effectively analyze both organized and unstructured data Create strategies to address company issues. 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. To succeed as a data scientist, you must, nevertheless, make a particular effort to apply soft skills. You'll have a personal mentor who will keep track of your development. 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 Melbourne. Cleaning and validating data to ensure that it is accurate and consistent. This curriculum prepares you to work in a variety of Data Science professions and earn top-dollar wages.

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 Melbourne

  • AstutePayroll | Location details: Level 1/325 Flinders Ln, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: astutepayroll.com | Contact Number (Helpline):
  • E2*(E2Language) | Location details: 20-22 Albert Rd, South Melbourne VIC 3205, Australia | Classification: Software company, Software company | Visit Online: e2language.com | Contact Number (Helpline):
  • AvaTraining | Location details: 105 Batman St, West Melbourne VIC 3003, Australia | Classification: Engineering consultant, Engineering consultant | Visit Online: avatraining.com.au | Contact Number (Helpline): +61 1300 754 699
  • CiscoSystemsAustraliaPTYLtd. | Location details: 14/101 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: | Contact Number (Helpline): +61 3 9659 4200
  • AcademiaInstitute | Location details: 399 Lonsdale St, Melbourne VIC 3000, Australia | Classification: Educational institution, Educational institution | Visit Online: academia21.com | Contact Number (Helpline): +61 3 9671 4755
  • PlanitTesting | Location details: Level 6, Tenancy 3/550 Bourke St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: planittesting.com | Contact Number (Helpline): +61 3 9067 7100
  • PlatinumProfessionalTraining | Location details: 605/343 Little Collins St, Melbourne VIC 3000, Australia | Classification: Training centre, Training centre | Visit Online: platinumaccg.com.au | Contact Number (Helpline): +61 3 9642 0393
  • CiscoSystemsAustraliaPTYLtd. | Location details: 14/101 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: | Contact Number (Helpline): +61 3 9659 4200
  • Altora | Location details: Level 19/15 William St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: altora.com.au | Contact Number (Helpline): +61 3 9329 7130
  • RMITSingleAndShortCourses | Location details: GPO Box 2476, Melbourne, VIC 3001, Australia | Classification: Department of education, Department of education | Visit Online: rmit.edu.au | Contact Number (Helpline): +61 3 9925 8111
  • TowerAustralianCollege | Location details: 53-55 Dryburgh St, West Melbourne VIC 3003, Australia | Classification: Educational institution, Educational institution | Visit Online: tower.edu.au | Contact Number (Helpline): +61 3 8374 7904
  • DVSConsulting&Services | Location details: 50 Queen St, Melbourne VIC 3000, Australia | Classification: Website designer, Website designer | Visit Online: | Contact Number (Helpline): +61 490 802 370
  • InstituteOfHealthAndNursingAustralia(NorthMelbourneCampus) | Location details: 203/187 Boundary Rd, North Melbourne VIC 3051, Australia | Classification: Educational institution, Educational institution | Visit Online: ihna.edu.au | Contact Number (Helpline): +61 3 9450 5111
  • MonarchInstitute | Location details: Lvl 22/535 Bourke St, Melbourne VIC 3000, Australia | Classification: Educational institution, Educational institution | Visit Online: monarch.edu.au | Contact Number (Helpline): +61 1300 738 955
  • RMITEnglishWorldwide | Location details: RMIT, Building 108, Level 10/235-251 Bourke St, Melbourne VIC 3000, Australia | Classification: English language school, English language school | Visit Online: rmittraining.com | Contact Number (Helpline): +61 3 9657 5800
  • 4amSoftwarePtyLtd | Location details: 480 Collins St, Melbourne VIC 3000, Australia | Classification: Software company, Software company | Visit Online: 4amsoftware.com.au | Contact Number (Helpline): +61 3 8610 6683
 courses in Melbourne
More than half of Melbourne's population has either one or both parents who were born overseas. There are always exciting things to do in Melbourne. To understand the academic year of each university , please contact the university directly. edu. edu. au Victoria University Polytechnic victoriapolytechnic. present and future occupations. Our diversity We are proud that Melbourne is home to one of the most harmonious and culturally diverse communities in the world. These partnerships provide students with hands-on experience and open doors to future employment and research programs. It is a safe and vibrant global city renowned for its livability, great beaches, friendly people, iconic highways, cultural experiences, a diverse food and wine scene and a dynamic student population.

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