Data Science and Machine Learning

BY
CodingNomads

Learn Data Science, Machine Learning, AI fundamentals through Learn Data Science + Machine Learning Online by CodingNomads.

Lavel

Expert

Mode

Online

Duration

4 Months

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based
Learning efforts 15-20 Hours Per Week

Course overview

The Learn Data Science + Machine Learning Online certification course is provided by CodingNomads. The online course in Learn Data Science + Machine Learning Online deals with topics such as Machine Learning algorithms, data science, data modeling, and evaluation, etc. Candidates who enrol in the course get to learn through the in-built study material that includes projects, quizzes, documentation pages, along video lectures. 

The Learn Data Science + Machine Learning Online certification syllabus takes around 12 weeks of time to get completed if students decide to spend 5-15 hours per week. Students need to have just 3 months of work experience to apply for the course. Also, students must have basic python coding skills and knowledge of algebra to get into the programme. The Learn Data Science + Machine Learning Online classes by CodingNomads can also be joined freely at zero cost. The Learn Data Science + Machine Learning Online course allows flexibility and can be attended by the student at any time depending upon their schedules. In the end, students get to acquire a certificate of completion. 

The highlights

  • 180 hours of course curriculum
  • 24+ Quizzes
  • 60+ video learning content
  • 12 DSML labs
  • Course available for free
  • 5-15 hours of time is required per week
  • Self-paced course
  • Certification of completion by CodingNomads

Program offerings

  • Projects
  • Quizzes
  • Assignments
  • Videos

Course and certificate fees

certificate availability

Yes

certificate providing authority

CodingNomads

Eligibility criteria

Work Experience

Students need to have a minimum of 3 months of coding experience.

Education

Students who wish to enroll in this Learn Data Science + Machine Learning Online course must have Python and OOP programming skills as well as basic Algebra. 

What you will learn

Machine learning Data science knowledge Data wrangling

Participants by the end of  Learn Data Science + Machine Learning Online programme, will master a varied range of concepts that are given below:

  • Students will learn how to build and run machine learning models.
  • Candidates will be able to gather and process data in the Learn Data Science + Machine Learning Online certification.
  • Students will learn about feature extraction from different data types.
  • Participants will learn about ensemble methods in the Learn Data Science + Machine Learning Online classes.
  • Students will learn how to handle missing data in the Learn Data Science + Machine Learning Online training.
  • Candidates will get to know about data wrangling and preprocessing.

The syllabus

Data science, ML, and AI fundamentals

  • How to think like a data scientist
  • Artificial intelligence- what's with all the hype
  • How to discover and present a compelling story
  • Why AI and Machine Learning are so important

Tools of the trade

  • Jupyter notebooks to create and share your documentation 
  • NumPy to perform numerical computing, including initialisation
  • Pandas to perform transformation and calculation of datasets
  • Mathematical and statistical functions
  • SciKit learn for Machine Learning
  • Matplotlib and seaborn for data visualization
  • Greek math notation, sums, and derivative reviews

Supervised learning

  • Linear regression: Bias variance tradeoff (overfitting vs underfitting), gradient descent, regularization, feature scaling.
  • Ensemble method: Bagging with random forests boosting with Adaboost

Unsupervised Learning

  • Clustering with K-means and DBScan
  • Dimensionality reduction with PCA

Model Evaluation & Validation

  • Training and test sets, baseline models, random seeds.
  • Classification with a decision tree: Gini impurity coefficient information gain ratio, regularization parameters
  • Classification metrics: Accuracy, precision, recall, f1-score, confusion matrices.
  • Hyperparameter tuning: Gridsearch, randomized  search K-fold, shufflespit, leave-one-out, stratification learning and validation curves  

Dealing with data

  • Feature extraction from different data types: Tabular, image, time series, natural language processing, computer vision
  • Data wrangling, cleaning, preprocessing
  • Data pipelines to avoid overfitting
  • Handling missing data
  • Normalisation and standardization

Admission details

Candidates can follow the given guidelines to get enrolled in the Learn Data Science + Machine Learning Online training:

Step 1- Click on the given link- https://codingnomads.com/course/data-science-machine-learning

Step 2- They must create their account on Coding Nomads.

Step 3- They must fill in the required details.

Step 4- They must pay the required amount and get started with the course.

How it helps

Candidates can join the Learn Data Science + Machine Learning Online certification course in online mode. The course is available as a free programme as well as in subscription mode. Students joining Learn Data Science + Machine Learning Online class will gain information on Machine Learning and Data Science. The video sessions can be completed within the period of 12 weeks and can be accessed at any time. Students will be able to receive a certification by the time the course comes to an end. 

Students who acquire the certificate will get Learn Data Science + Machine Learning Online certification benefits. The certification is helpful in the job hunting process of the students. Candidates can apply for entry-level jobs or internships in the market by completing the programme. The certification can be used to pursue any other course that belongs to a similar industry or a higher level of the programme from the same platform. Students can make their CVs or resume attractive by including the achievement of the certification as highlights. This helps the CV look more promising and boosts the profile of the candidate that leading to creating a great first impression on the recruiter. 

FAQs

Will I be given full access to online Learn Data Science + Machine Learning Online in free mode?

No, students will gain partial access to the curriculum if they join for free.

What if I want to pay the course fee in instalments?

Students can pay the Learn Data Science + Machine Learning Online fee in instalments by choosing the suitable option.

What is the study material used in the Learn Data Science + Machine Learning Online certification syllabus?

The study material used in the programme is interactive quizzes, discussions, video sessions, documentation pages, etc.

How can I pay the fee in Learn Data Science + Machine Learning Online certification?

The programme offers four different methods of fee payment. Students can choose any suitable method depending upon their preferences.

When can I apply for the Learn Data Science + Machine Learning Online programme?

The course is open for all interested students and they can apply at any time for the course.

Will I get university credits for completing this Learn Data Science + Machine Learning Online certification ?

No, you will not get any university credits since it is not offered in the course. 

Can I apply for jobs after course completion?

Yes, there are various job options after completing the course.

What is the prerequisite to apply for the programme?

The programme requires prior knowledge of Python and OOP coding skills and 3 months of coding experience.

Is it important to have work experience for Data Science and Machine Learning by Coding Ninjas?

Yes, a work experience of a minimum of 3 months is required for the Learn Data Science + Machine Learning Online course.

How many projects are there in the course?

The Learn Data Science + Machine Learning Online syllabus includes 1 capstone project and 12 mini projects. 

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