Machine Learning

Master your career path with the Machine Learning course

To become an expert Machine learning professional, you need the right learning platform. This Machine Learning certification program brings adepts you with the knowledge base that enhances your skills and equips you to define your professional growth in a positive direction.

Modules

7 Modules

Completion Time

5 months (5-7 hours per week)

Lessons

85

Machine Learning Course

Empower your career growth with Machine Learning/ Machine Learning: New Age Skill/ Create algorithm of a successful career with Machine Learning / Be More Than A Tech Geek with Machine Learning

Disclaimer- The machine learning course is a subset of Pickl’s data science program. This course provides all the information on machine learning that makes comprehension of data science easy for you.

Roadmap of Machine Learning Program

The Machine Learning certification program has been curated in tandem with the demand in the industry. The curriculum entails fundamental aspects of Machine Learning along with its practical implications.

Pickl’s Machine Learning certification is designed to help you understand the underlying concepts of Machine Learning under the practical realm. This Machine Learning course aims to equip you with all the necessary skills that will bring you to the forefront while helping you learn all the concepts and applications.

Machine Learning Certification Key Features

Benefit of classroom learning and practical implementation

Real-world case study for better comprehension of ML and allied concepts

The course covers elemental and practical aspects of Machine Learning

Course curated and delivered by machine learning experts and industry moguls

Placement and career assistance after course completion

Machine Learning Course Module

Introduction to Machine Learning

  • Real-Life Example
  • Technical Definition

How does a Machine Learn?

  • Basic ML Terminologies
  • Supervised
  • Unsupervised
  • Semi-supervised
  • Reinforcement learning

Preparing Data for modelling - EDA

  • Data Summarization
  • Range
  • Measures of Central tendency
  • Data distribution
  • Box Plots
  • Univariate
  • Bar Charts
  • Histograms
  • Pie Charts
  • Multivariate
  • Scatterplots
  • Correlation: basics
  • Correlation: Math

Preparing Data for modelling - Feature engineering and selection (Theory + Practical)

  • Encoding categorical variable
  • Categorial data : Ordinal vs Nominal
  • Basic Encoding methods
  • Imputing missing data
  • Imputation: Numerical
  • Imputation: Categorical
  • Advanced Imputation methods
  • Handling Imbalance data
  • Imputation for Numerical
  • Imputation for Categorical
  • Advanced Imputation methods
  • Combining Features using Mathematical computation
  • Feature selection

Gradient Descent

  • Hypothesis-parameter curve
  • Basic Intuition
  • Mathematics Behind
  • Loss curve and Learning rate

Bias Variance tradeoff

  • Basic Intuition
  • BMathematics Behind

Who Can Join The Machine Learning Certification Program

The Certified Machine Learning Program is apt for
  1. Fresher
  2. Engineering & Management Students
  3. Professors
  4. Software Engineers & Architects
  5. Any working professional willing to upskill

Machine Learning Certification Benefits

  1. Gain an in-depth understanding of concepts of Machine Learning
  2. Practical application of Machine Learning
  3. Gain a competitive edge
  4. Give more weightage to your profile
  5. become eligible for a higher pay package
What's In It For You?

Pickl's Machine Learning program has been curated to offer theoretical and practical excellence. This program aims to create a skilled workforce who can leverage their knowledge and skills to different industries. With Pickl’s Machine Learning course

  • Be a pro in Machine Learning with a professional certification
  • Build your portfolio by working on real-world projects
  • Get the placement assistance and complete guidance during and after the course.
Catalyze Your Career Growth With Pickl.ai

Whether you are a fresher or a working professional, acquiring a new skill set is always a positive move. Pickl's Machine Learning course has been curated to provide the right knowledge and expertise.

For more information and enrollemnt process connect with us today.

Frequently asked questions

To start your journey in a Machine Learning course, you must have basic knowledge about mathematics. If you know Python, it will simplify your learning journey.
Learning about new technology and its implementation can be challenging, but with the right guidance and support, you can easily sail through. The Machine Learning course by Pickl.ai has been prepared to provide a complete learning and understanding of the core concepts and their implementation. It covers the fundamental and advanced technical aspects of Machine Learning, thus simplifying your learning process.
Yes, if you want to excel as a Machine Learning expert, you must know Python. As a part of your Machine Learning curriculum, you will have to deal with data, hyper-parameters, models, optimizing, understanding the algorithms, validations, vectorising your variables etc. And with Python, your task becomes simplified.
Certainly, if you are inclined to learn about data, automation, and algorithms, Machine Learning can be the right guiding line. As per the reports (2019) of Indeed, Machine Learning was the top job in terms of growth prospects, salary, and demand. Between 2014-2018, the demand for Machine Learning experts has increased by 344%. And hence, it's a lucrative career opportunity..
If you wish to start a Machine Learning course, you must first enroll with a credible learning platform. There are online and offline classes. However, if you wish to get the benefit from the best learning experience at your suitable time, Pickl.ai's Machine Learning course will be the best option. The course is delivered by industry experts, and Pickl also offers placement assistance, thus making it easy for you to move ahead confidently in your professional life.
When it comes to the learning pace, it may vary from one individual to another. But the right guidance and assistance can certainly catalyze the learning process. Pick.ai ensures that all the conceptual learning is backed by practical application to make things easier for the students to comprehend and implement.
Pickl.ai's Machine Learning course will cover the following topics:
  • Introduction to Machine Learning
  • How does a Machine Learn?
  • Preparing Data for modeling - EDA
  • Preparing Data for modeling - Feature engineering and selection (Theory + Practical)
  • Gradient Descent
  • Bias Variance trade-off
If you want to become a certified Machine Learning professional, you must enrol for the Machine Learning certification program. Pickl.ai provides an industry-oriented learning program that is recognized by industry and experts. After successfully completing this program, you will become a certified Machine Learning expert.
Yes, for the Machine Learning course, you must be well-acquainted with the key concepts of mathematics.
Lack of programming language expertise can deter people from pursuing the Machine Learning course. However, with the rise of MLaaS (Machine Learning as a service), certain tools will help you start the Machine Learning journey. These tools are used for Machine Learning applications in the business. These include predictive modelling and clustering.
While many programming languages are used by developers, data scientists and Machine Learning experts, Python takes the lead in this.
Yes, even a fresher can become a Machine Learning engineer. Pickl’s Machine Learning course for dabbler has been curated to suit the knowledge and skill base of a fresher, and it helps them on their way to becoming a Machine Learning engineer. After completing the dabbler program, you can step ahead and join the apprentice program.
By 2024, it is expected that the Machine Learning jobs will be worth $31 billion. This shows the growth prospects of a career in this field. After the completion of the Machine Learning course, one can become :
  • Machine Learning engineer
  • Human-centered Machine Learning designer
  • Computational linguist
  • Data scientist
  • Software developer
  • Business intelligence developer
Well, the primary objective of both these technologies is to ensure maximum productivity and flawless work. However, when it comes to ensuring better decision-making, lesser error, and higher productivity, companies use both. AI ensures lesser error and ML enhances data integrity. The key objective is to make the business run seamlessly and deliver outstanding outcomes. And hence both these technologies complement each other.
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Our data science and machine learning stalwarts

  • High School Student

  • Non Tech Enthusiast

  • Graduate Engineer

  • MBA Professional

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