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Data Science and Machine Learning Course

Course Description

Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors. In this course, part of our Professional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system. You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning. The program is a blend of data science, deep learning, business analytics and visualization with the application of advanced analytics models for artificial intelligence, deep learning and cognitive computing. Designed to give students a comprehensive analytics education with projects and seminars by industry leaders and hands-on learning.

What you'll learn

  • The basics of machine learning
  • How to perform cross-validation to avoid overtraining
  • Several popular machine learning algorithms
  • How to build a recommendation system
  • What is regularization and why it is useful

Basic Eligibility

Graduate in Engineering in IT / Computer Science / Electronics / IT & Telecommunications / Electrical / Instrumentation and other computer associated streams. No year down & no paper down from the Candidates to get placements. 60 % marks as aggregate in qualifying examination. OR Post Graduate Degree in Engineering Sciences with corresponding basic degree (e.g. MSc in Computer Science, IT, Electronics) with 60% marks as aggregate in qualifying examination. Also Equally Required:
  • Strong liking for basic Mathematics, Logical Reasoning
  • Analytical Bent of Mind
  • Desire to Learn
  • Willing to put sincere efforts and time to pick up new concepts
  • Job Opportunities

    • Data Scientist & Machine Learning Engineer
    • Design Engineer
    • Data Engineer
    • Data Scientist
    • Data Science Specialist
    • Machine Learning Engineer
    • Senior Data Scientist
    • Data scientist visualization

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Data Science and Machine Learning Course

>>Introduction
  • What is Data Science
  • - What is Data Science composed of?
    - Fields of Study in Data Science, and Relationships between them
  • Role of Machine Learning in Data Science
  • Data: Sources, Exploration, Modeling, Visualization
>> Mathematics and Statistics Foundation
  • Brief introduction to Octave
  • Mathematics
  • - Scalars, Vectors, Matrices
    - Matrix Operations, Matrix Relationships
    - Eigenvalues, Eigenvectors
    - Dimensionality Reduction (PCA)
    - Basic Calculus
      - Limits
      - Derivatives
    - Statistics
      - Mean, Mode, Median
      - Variance, Standard Deviation
      - Probability
       - Events, Sample Space, Random Variables
       - Mutually Exclusive Events
       - Venn Diagrams
       - Bayes Theorem
    - Inference (Introduction)
      - Sampling, Hypothesis Testing
>> Python Programming
  • Hands on with Python
  •   - Getting Started with Jupyter Notebook
      - Shell Operations, Variables, Strings, Simple I/O
  • Programming Semantics
  •   - Control Structures, Loops
      - List, Tuple, Dict, Set
      - List and Dict Comprehension
  • Functions and Modules
  •   - Function as objects
      - Standared Library, pip
  • File/Data Handling, Exceptions
  • Functional Programming
  • Object Oriented Programming
  • Python Programming Mini Project
  • Python Libraries for Machine Learning
  •   - Numpy
       - Scalars, Arrays
       - Array Indexing, Operations
       - Example Application: Hands on with Real world Dataset
  • Pandas
  •   - Data Frames, Series, Index ObjectsM
      - Missing Data
      - GroupBy
      - Example Application: Hands on with Real world Dataset
  • Matplotlib
  •   - Visualization
      - Line plots, Histograms, Box plots, Scatter plots
      - Introduction to Seaborn
      - Example Application: Hands on with Real world Dataset
  • Scikit-learn
  •   - Estimator
      - fit, predict
      - Transformers
      - Example Application: Hands on with Real world Dataset
>>Machine Learning
  • Regression
  •   - Simple Linear Regression
      - Multiple Linear Regression
      - Decision Tree Regression
      - Example Application: Hands on with Real world Dataset
  • Classification
  •   - Logistic Regression
      - K-Nearest Neighbour (KNN)
      - Support Vector Machine (SVM)
      - Naive Bayes
      - Evaluating Classification Model Performance
      - Example Application: Hands on with Real world Dataset
  • Clustering
  •   - K-Means Clustering
      - Example Application: Hands on with Real world Dataset
  • Artificial Neural Networks (ANN)
  • Applying Machine Learning: Deployment
  •   - Python Requests
      - Python Flask
      - Deployment with Cloud Services

Why learn Machine learning?

  • Machine learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of machine learning
  • The machine learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period

What are the basic qualifications required for doing course in Data Science and Machine Learning?

Graduate in Engineering in IT / Computer Science / Electronics / IT & Telecommunications / Electrical / Instrumentation and other computer associated streams.

OR

Post Graduate Degree in Engineering Sciences with corresponding basic degree (e.g. MSc in Computer Science, IT, Electronics) with 60% marks as aggregate in qualifying examination.

Also Equally Required:

  • Fair understanding of the basics of statistics and mathematics
  • Analytical Bent of Mind
  • Desire to Learn
  • Willing to put sincere efforts and time to pick up new concepts

Do I require any knowledge in computer programming?

Basic knowledge of C programming is required.

Will I get Internship after completion of my “Data Science and Machine Learning Course”?

Yes. You can get Internship but It will be based on your performance throughout the course and depth of knowledge.

Who should take this Machine Learning Training Course?

There is an increasing demand for skilled machine learning engineers across all industries, making this Machine Learning certification course well-suited for participants at the intermediate level of experience. We recommend this Machine Learning training course for the following professionals in particular:
  • Developers aspiring to be a data scientist or machine learning engineer
  • Analytics managers who are leading a team of analysts
  • Business analysts who want to understand data science techniques
  • Information architects who want to gain expertise in machine learning algorithms
  • Analytics professionals who want to work in machine learning or artificial intelligence
  • Graduates looking to build a career in data science and machine learning
  • Experienced professionals who would like to harness machine learning in their fields to get more insights

What skills will you learn with our Machine Learning Certification Course?

  • Master the concepts of supervised and unsupervised learning, recommendation engine, and time series modelling
  • Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach that includes working on four major end-to-end projects and hands-on exercises
  • Acquire thorough knowledge of the statistical and heuristic aspects of machine learning
  • Implement models such as support vector machines, kernel SVM, naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-means clustering and more in Python
  • Comprehend theoretical concepts and how they relate to the practical aspects of machine learning

What is the duration for the course in Data Science and Machine Learning?

The duration for our course is 60 hours.

Can I attend classes in evening or weekend?

Yes, we have flexi-timing courses which are suitable for students as well as working professionals; we have weekday/part-time and weekends courses.

Do you provide placement assistance?

Yes, we provide 100% placement assistance. We have placement cell which caters specifically to placement of the students. Bicard provides personality development training to students specifically for better placement.

What are the job prospects after doing course in Data Science and Machine Learning?

Job prospects are very good.

I am a final year engineering student. Can I attend the course?

Yes, you can attend the course.

What are the fees for courses in Data Science and Machine Learning?

The charges are Rs. 25,000/-

Do you provide online courses?

No, we do not provide online courses.

Where are the various centres of Bicard?

We have only one center in Pune

Are any projects included in the course?

Yes, students have to take up real time projects for hands on experience. It is guided by our industry-experienced faculties.

Do you provide any industrial training?

Yes, we provide 2 months Industrial Training wherein you can get experience in various real time projects and to work efficiently in a team and manage development in a particular delivery time. For further information, you can contact our Admission Head.

What is the expertise level of the faculties?

Our all faculties have more than 15 years of experience from the industry and training. They have good domain as well as subject knowledge with practical experience.

Will I be given certificate on completion of the course?

Yes, Bicard provides the certificate.

Are any course materials provided?

We provide our faculties suggested pool of online resources.

What is the fees payment procedure?

The fees payments for the entire course can be done in Cash/Cheque/Online Payment/Credit or Debit Card.

Does Bicard provide any training for facing the interviews?

Yes, Bicard, along the course, provides personality development training which every students should have for facing the interview. In addition to that, other skills like team work, effective communication – verbal and written etc. are being taught through real-time projects.

Where can I see the course contents of the course?

You can see all the courses’ contents on our website

Is there any entrance examination for the admission?

There is a direct admission for the course.

What is the syllabus for entrance examination?

You can refer to our website where we have given detailed syllabus for entrance examination for our various courses.

Our New Batches are Starting in February, 2020. Please call us on 9595605544 || 020 40059500 || 020 40059600 to know more

We totally understand that each student is different and each student has different problems, which we need to tackle. Keeping this in view, we have designed different packages to meet your needs and timings.
  • Weekend batches: We have a special weekend batches for the working professionals, who are tied up on weekdays.
  • Fast-track batches: To complete the course in a brief time with detailed training.
  • Specialized corporate batches: In this special batch, we only cater the training needs of the corporate employees.
Upcoming Courses & Batches

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