Course Learning Outcomes :-

On completion of this course, the students will be able to:

• Understand the basic concepts of ML.
• Understand how to use different python libraries in ML.
• Work with different Regression and Classification Algorithms.
• Perform syntax and semantics in ML with Python.
• Ability to design and analyse various ML algorithms.
• Apply different concepts of ML in other application areas.

The following topics will be covered in our Data Science for Juniors Training. 

Descriptive Statistics

• Measures of Central Tendency: Mean, Median, Mode
• Measures of Dispersion: Range, Interquartile Range, Standard Deviation
• Correlation Analysis: Pearson Correlation Coefficient, Spearman Correlation Coefficient
• Visualization: Boxplot, Histogram, Scatterplot

Introduction to Probability

• Conditional Probability, Bayes Theorem
• Probability Distributions: Binomial, Poisson, Normal

Introduction to Machine Learning

• Types of Machine Learning
• Machine Learning Algorithms
• Applications of Machine Learning

Preparing to run ML algorithms

• Feature Extraction and Transformation
• Model Training and Optimization
• Model Evaluation and Selection

Regression Algorithm

• Simple Linear Regression
• Multiple Linear Regression
• Polynomial Regression
• Ridge Lasso Elasticnet
• Mini Project

Classification Algorithm

• Logistic Regression
• K-NN
• SVM
• Decision Tree Classification
• Random Forest Classification
• Mini Project

Clustering Algorithm

• K-Means
• Hierarchical Clustering
• Mini Project

Natural Language Processing

• Text Preprocessing
• Tokenization
• Parsing
• Semantic Analysis
• Sentiment Analysis
• Mini Project

Major Project (Retail/Healthcare/Finance)

• Application of all the concepts to develop a project

Prerequisites:-

• Python for Junior course: Knowledge of Python is mandatory to take up this course
• The student should have good logical and reasoning skill.

Key Features:

Training Type: Online Live Interactive Session.

Experienced Faculty.

1 ON 1 Sessions.

Duration 30 Hours.

Access to Class Recordings.

Weekday / Weekend Classes.

Evening Schedule:

3 Days / Week

8:30 PM – 9:30 PM EST

9:00 PM – 10:00 PM EST

9:30 PM – 10:30 PM EST

10:00 PM – 11:00 PM EST

Morning Schedule:

3 Days / Week

10:00 AM – 11:00 AM EST

10:30 AM – 11:30 AM EST

11:00 AM – 12:00 PM EST

11:30 AM – 12:30 PM EST

Please contact us, If you are looking for different schedule or need more information.

 Inquiry Now 

USA: +1 734 418 2465 | India: +91 40 4018 1306

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