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Data Science Mentorship Program (200+ hours)

Original price was: $79.00.Current price is: $29.00.

Price: 29.00 USD | Size: 68.9 GB |   Duration : 200+ Hours  | 133 Video Lessons 

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ENGLISH | INSTANT DOWNLOAD | ⭐️⭐️⭐️⭐️⭐️ 4.9

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Description

Price: 29.00 USD | Size: 68.9 GB |   Duration : 200+ Hours  | 133 Video Lessons 

BRAND: Expert TRAINING | ENGLISH | INSTANT DOWNLOAD | ⭐️⭐️⭐️⭐️⭐️ 4.9

 

Data Science Mentorship Program

 

Requirements

 

  • A laptop and an internet connection to attend live classes.
  •  Basic Mathematical knowledge(not much).
  •  A zeal to learn complex topics.

 

About the course

Data Science Mentorship Program is a 7-month long mentorship program designed to make you an industry-ready data scientist. The core philosophy behind the design of the program is its hands-on approach. Each module under the program consists of a plethora of assignments and projects. During the course, you would be exposed to industry-relevant curriculum, tools and libraries. We would also be doing a bunch of real-life case studies to make sure you learn the concepts practically. Along with the course, we would also be focusing on interview preparation. To go with this, we will also be providing doubt support to the paid members of the course, by conducting doubt clearance classes. Apart from academics, we would also focus on portfolio building and career counselling. We strive hard to impart quality education at an affordable price and we believe we can help you in your journey to becoming a kickass data scientist. Hope to meet you in the program. Happy Learning!

 

What You Will Learn

Python and SQL

Data Science

Data Visualization

Feature Engineering

Model Deployment and monitoring

Machine Learning Algorithms

Working on Real-life projects

Exploratory Data Analysis

 

Course Curriculum

Python for Data Science

  • Fundamentals of Python
  • Numpy
  • Pandas

 

Data Visualization

  • Basic Statistics
  • Matplotlib
  • Seaborn

 

SQL for Data Science

  • Database Basics
  • SQL Basics
  • Advanced SQL

 

Data Analysis Process 

  • Data Acquisition
  • Data Cleaning
  • Data Wrangling & EDA

 

Basic Machine Learning

  • Machine Learning Theory
  • ML Metrics
  • Small End to End project

 

Mathematics of Data Science

  • Advanced Statistics
  • Linear Algebra
  • Probability & Calculus

 

Machine Learning Algorithms- 1

  • Linear & Logistics Regression
  • SVM & KNN
  • Naive bayes  & Bagging
  • Decision Tree & Adaboost
  • Random Forest

 

Machine Learning Algorithms- 2

  • Gradient Boosting & XgBoost
  • PCA & K-Means
  •  Hierarchical Clustering
  • DBSCAN
  • T-sne

 

Practical Machine Learning – 1

  • Bias Variance Trade-off
  • Regularization
  • Cross Validation
  • Working with Missing Data
  • Feature Scaling & Encoding

 

Practical Machine Learning – 2

  • Feature Transformation
  • Pipelines
  • Date and Time
  • Feature Construction
  • Feature Selection

 

Practical Machine Learning – 3

  • Model Tuning
  • Imbalanced Datasets
  • Multicollinearity
  • Data Leakage
  • Working with large dataset

 

Model Productionalization & Deployment

End-to-End Case Studies

+ Many More

Who is this course for

 

01.

Industry professionals targeting to enter Data Science

02.

Students trying to make a career in Data Science

03.

High School students who are passionate about Learning Data Science

04.

Individuals with career gaps looking for a pivot in their career

 

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